National energy security, rising energy prices, increasingly competitive global markets, and stringent regulations for environmental emissions are the primary driving forces in the search for sustainable and economically viable technologies that incorporate efficient and clean approaches to energy conversion and utilization.  Internal combustion (IC) engines are the prime movers of choice when high power densities and efficiencies are desirable.  Because of relatively cheap fuel prices in the last few decades, IC engines had been optimized for high power densities and low emissions.  However, in recent years, with escalating fuel prices and concerns about sustainability, engine efficiency has assumed greater importance.  Over the last 150 years since the invention of the IC engine, great strides have been made in improving the fuel conversion efficiency of and reducing emissions from the IC engine. Further improvements in fuel conversion efficiency require a system-level analysis of the various losses encountered in the IC engine.  This analysis can begin with thermodynamic modeling of the IC engine.  Traditional first law–based thermodynamic models facilitate accurate energy accounting; that is, they are useful in estimating the net losses associated with the combustion process.  However, these models do not provide estimates of how much of the wasted energy is recoverable as useful work or exergy.  This requires second law–based models that track the irreversibilities associated with various processes that destroy fuel chemical exergy.  There are two pathways for better utilization of the chemical exergy of the fuel.  The first focuses on minimizing exergy destruction in the combustion process.  The second pathway involves tapping the exhaust exergy to obtain further improvements in the thermal efficiency of the prime mover.  This can be achieved by using a bottoming organic Rankine cycle (ORC). Waste heat recovery (WHR) using ORC involves the utilization of the sensible enthalpy of the hot exhaust from an IC engine to heat an organic fluid, preferably to saturated/superheated vapor, after which the sensible enthalpy of the vapor is used to obtain additional useful work from a turbine. Therefore, in general, exhaust waste heat recovery from stationary engines using ORC has the potential to increase fuel conversion efficiency.

ORGANIC RANKINE CYCLE ANALYSIS

Figure 1 shows a basic ORC coupled as a waste heat recovery cycle to a stationary engine.  The exhaust from the engine is assumed to be routed through the evaporator, where heat transfer occurs between the exhaust stream and the organic working fluid.  A counterflow heat exchanger (evaporator) configuration is considered to maximize heat transfer between the exhaust and the organic fluid.  Thermodynamically, this is a preferred configuration because the temperature difference between the hot fluid and the cold fluid is minimized, reducing exergy destruction.  The heated organic fluid then is expanded in a turbine, heat is rejected to the ambient in the condenser, and the cooled working fluid is pumped back into the evaporator.

An important factor that affects the efficiency of an ORC is the selection of the organic working fluid.  The working fluid must be selected carefully on the basis of safety and technical feasibility.  A good working fluid should have low toxicity, good material compatibility and fluid stability limits, and low flammability, corrosion, and fouling characteristics.  Refrigerants are good candidates for ORC applications as a result of their low toxicity characteristics.  Organic fluids can be classified as dry, wet, and isentropic, depending on the slope of the saturation curve in the T-s diagram (Figure 2).  On a T-s diagram, a dry fluid has a positive slope, a wet fluid has a negative slope, and an isentropic fluid has infinitely large slopes.  Dry and isentropic fluids show better thermal efficiencies than wet fluids.  One of the reasons for this is that dry and isentropic fluids do not condense after the fluid goes through the turbine, as opposed to wet fluids.  For the case presented, R113, which is a dry fluid, was selected as the working fluid because it has been shown to be a good candidate for ORC applications.¹ Further, it is assumed that waste heat from the engine will be used to heat the organic fluid from subcooled liquid to saturated vapor.  This condition was preset since previous studies have reported that dry organic fluids do not need to be superheated.²

COMBINED ENGINE-ORC CONFIGURATION

As was mentioned above, exhaust waste heat recovery from stationary engines using ORC has the potential to increase fuel conversion efficiency and reduce break specific emissions.  The fuel conversion efficiency of the engine, FCEeng, and the engine-ORC configuration, FCEeng-ORC, can be estimated as follows:

where LHVfuel is the lower heating value of the fuel, mfuel is the mass of fuel, and Weng and WORC are the engine power and ORC power, respectively.

Therefore, it is clear that exhaust WHR using an ORC results in higher power with the same fuel energy input into the system.

Figure 3 illustrates the engine efficiency of a dual fuel (diesel pilot-ignited natural gas fired) engine* (from experiments³), the combined engine-ORC efficiency (predicted from ORC simulation), and the percentage of increase between the two cases at representative diesel pilot injection timings of 20°, 40°, and 60° BTDC (before top dead center) for a single-cylinder Caterpillar 3401 (1Y SCOTE) engine with simulated turbocharging operating at half load (21 kW power). From this figure, it can be seen that using a combined engine-ORC configuration, the thermal efficiency can be incremented by approximately 10 to 13 percent of the baseline values for all injection timings.

An important parameter that affects the combined engine-ORC system performance is the pinch point temperature difference (PPTD), which is defined as the difference between the exhaust gas temperature and the temperature at which the organic fluid first begins to vaporize (Figure 4). This is the smallest temperature difference in the evaporator (ORC heat exchanger), and it defines the performance limits of the ORC heat exchanger. The T-∆H diagram used for the pinch point analysis is illustrated in Figure 4.  The heat transfer rate across the ORC heat exchanger is proportional to the PPTD. As the PPTD increases, the mass flow rate of the organic fluid decreases, and this results in poor utilization of the exhaust energy.  To accomplish heat transfer across smaller PPTD values, larger heat exchanger areas are required.  This leads to larger and more expensive heat exchangers. However, the exergy efficiency of heat transfer across a smaller temperature difference is much higher (i.e., this leads to lower exergy destruction). Therefore, there is a clear cost versus efficiency trade-off in selecting evaporators in ORC design.

Another important parameter that affects the performance of the exhaust waste heat recovery using an ORC is the evaporator temperature and evaporator effectiveness. This temperature has to be selected properly to avoid condensation of water in the evaporator. It is important to prevent water condensation to reduce the potential for corrosion in the evaporator tubing. In general, the first and second law efficiencies of an ORC increase with the increment of the evaporator temperature, which will also increase the overall performance of the combined engine-ORC system. Regarding the evaporator effectiveness, it is clear that as the evaporator effectiveness increases, the PPTD decreases.  These trends also indicate that higher exergy efficiencies are possible by choosing higher evaporator effectiveness values. However, as was discussed above, this entails a higher cost as a result of the fact that larger evaporators are needed to facilitate heat transfer across smaller temperature differences.  However, favoring lower evaporator effectiveness presents a practical problem of water condensation in the evaporator tubing. Therefore, a balance point has to be found between the evaporator temperature and the temperature at which condensation will not be present.

CONCLUSIONS

The fuel conversion efficiency of stationary power engines can be improved by using organic Rankine cycles to recover the exhaust waste heat.  The operation of a combined engine-ORC system yields a fuel conversion efficiency improvement of the order of 10 to 15 percent.

* A diesel pilot-ignited natural gas engine employs small amounts of diesel fuel injected at a pre-determined time (injection timing) into the combustion chamber to ignite the inducted natural gas-air mixture.

REFERENCES

1. Mago, P. J., Chamra, L. M., and Somayaji, C. “Analysis and Optimization of Organic Rankine Cycles.” IMechE Journal of Power and Energy, vol. 221, no. 3, May 2007, pp. 255–263.
2. Mago, P. J., Chamra, L. M., Srinivasan, K., and Somayaji, C. “An Examination of Regenerative Rankine Cycles Using Dry Fluids.” Applied Thermal Engineering, vol. 28, no. 8–9, June 2008, pp. 998–1007.
3. Srinivasan, K. K., Mago, P. J., Zdaniuk, G. J., Chamra, L. M., and Midkiff, K. C. “Improving the Efficiency of the Advanced Injection Low Pilot Ignited Natural Gas Engine Using Organic Rankine Cycles.” ASME Journal of Energy Resources Technology, vol. 130, June 2008, pp. 022201-1–022201-7.

Mass rapid transport systems (MRTSs) are needed to support sprawling growth in urban India. Inadequate MRTSs have led to a rise in the use of personal vehicles, causing an increase in road congestion, delays, fuel use and environmental pollution. Delhi Metro Rail Corporation (DMRC)  is changing the face of transportation in that city with the launch of its Metro Rail project. The DMRC’s mission is to cover the New Delhi area with a metro rail network, planned in four phases, with a target date of 2021 for completion of the last phase. It consists of a network of underground, at-grade, and elevated infrastructure. Developmental projects such as this often result in environmental degradation, but DMRC broke from that pattern by implementing an Environmental Management System (EMS) as per ISO 14001 standard; it was awarded ISO 14001 certification for environmentally friendly construction practices. It is the second metro system in the world, after the New York subway system, to achieve this standard and the first to receive it in the construction stage.

© Delhi Metro Rail Corporation Ltd. (DMRC)

This milestone was achieved through DMRC’s determination to adopt environmentally-friendly construction practices, striking a balance between preventing ecological degradation and minimizing inconvenience to the public. The work was facilitated by the U.S. Agency for International Development and the Confederation of Indian Industry. The environmental policy adopted by DMRC highlights the organization’s commitment to promote environmental conservation and its efforts to create environmental awareness among among DMRC employees, contractors and metro users.

DESCRIPTION OF CHALLENGE AND STATEMENT OF PROBLEM OR NEED

The ISO 14001 standard has been adopted in the construction of Phase 1 and Phase 2 of the Delhi Metro Project. Challenges faced while designing and implementing EMS ISO 14001 during construction are described below.

Loss of Green Cover

No endangered species or forest area existed along the MRTS alignment or its corridors. Most of the trees, which were planted along the roads decades ago, provided clean air and acted as carbon sinks. Loss of green cover could affect the local ambient air quality, temperature, and humidity levels adversely.  The primary concern was to reduce the environmental degradation in the name of development.

Dust Generation

Fugitive emissions and dust generation from construction activities such as transportation of earth, loading and unloading of material, and movement of heavy machinery such as compactors, rollers, water tankers, and dumpers were a visible challenge. The level of suspended particulate matter (SPM) was high within a few meters from the source within and around the site from the earthwork activities and material handling.

Soil Erosion and Disposal

Runoff from unprotected excavated areas, quarry sites, and underground tunnel faces can result in excessive soil erosion, especially in areas where excavation is susceptible to erosion.  The excavation of soil is done mainly for cut and cover and tunneling and foundations. The soil left over after the filling is a challenge because of the extent of the project.

Solid Waste

The range of solid waste during construction is varied, including large quantities of earth, construction spoils (concrete, bricks) waste materials such as metal, scraps, plastic, and paint scrap (from utilities, welding and electrical works, and contractor camps). Leakage from used lube oil, paint, and chemical containers could be a potential source of water pollution.

Impact from Noise

The baseline noise levels are likely to increase during the preconstruction and construction phases of the activities involving site clearing and construction operations. During construction, there may be high noise levels as a result of pile driving and the use of compressors and drilling machinery. Diesel generator (DG) sets, vent shafts, and loading and unloading activities all contribute to the increase in the ambient noise level.

Impact on Water Quality

Water requirement for the construction are met from bore wells along the route alignment. Spillage of earth, used water from stone crushing, oils and greases, sewage waste, chemicals, and concrete agitator washings can pollute water if they leach into surface and the underground water. High total suspended solids is a primary concern in regard to water quality, considering its use in washing, dust suppression, and other construction activities.

Impact on Air Quality

Air pollution is due mainly to fugitive emissions and dust generation from various construction activities and vehicular emissions.  During the construction phase, SPM is expected to be the main pollutant associated with the earthwork activities, vehicular movement, and material handling.

DESCRIPTION OF SOLUTION AND METRICS FOR SUCCESS

Elaborate environmental impact assessment studies have been conducted for every segment in both phases of the project. Environmental management and monitoring plans were established to manage the environmental impacts arising from the project.

Compensatory Afforestation

Through refinement of the alignment and the moving of smaller trees, DMRC succeeded in reducing environmental degradation. Because an extensive amount of green cover is affected during the site-clearing operation (the construction phase), a manual count of the existing trees on every median has been carried out to identify the number of the trees that are likely to be affected and/or cut during the construction phase. For every tree cut during construction, the DMRC is planting ten trees as compensatory afforestation.  The Metro has undertaken compensatory afforestation with an 83 percent survival rate at Isapur, Najafgarh, Kakraula, and other sites. It is paying for the planting and fencing of indigenous tree species in two other sites. DMRC’s environmental policy statement emphasizes conservation and enhancement of green cover.

Dust Control

SPM is reduced by installing dust screens and hoardings alongside the construction area and doing regular water sprinkling during material movement. Full-height fences, barriers, and barricades were erected around the site to control dust during excavation. During transportation of debris and muck from construction sites, trucks were covered and loaded with sufficient free boarding space left at the top to avoid spills through the tailboard or sideboards.

Mitigation of Soil Erosion and Proper Disposal

Mitigation measures include planning, timing of cut and fill operations (postponed during monsoons), and revegetation. The blasting technique should be consistent not only with the nature and quality of the rock but also with the location of the blasting. Techniques to minimize dust and prevent fly rock are used. The excavated soil is used for backfilling or is transported in covered trucks to designated disposal sites or low-lying project areas that are compressed and leveled.

Solid Waste Management

To reduce construction spoils, the layouts of batching plants and casting yards are designed for the smooth flow of unloading and stacking of the aggregates, reinforcement and cement, transportation of concrete, and casting, stacking, and loading of the segments on the trucks. The rest of the waste is segregated and sold to authorized recyclers. The waste management program with designation of areas for segregation and temporary storage of reusable and recyclable materials is maintained by the contractors at the site.

Noise Control

Noise control can be achieved by means of automation, protective devices, noise barriers, soundproof compartments and control rooms, and job rotation. A site-specific noise-monitoring control plan guides noise management and alters the scheduling to minimize noise. For elevated corridors, a track structure without ballast is supported on two layers of rubber pads to reduce noise and vibrations. In addition, baffle wall for the parapets has been constructed up to the rail level to reduce sound levels.

Water Management

Wastewater from the construction site is not discharged from the site into water bodies by the contractors. Any water obtained from dewatering systems installed in the works is reused for construction purposes or discharged to the drainage. Adequate sanitary facilities and appropriate refuse collection and disposal systems are maintained. All water and waste products (surface runoff and wastewater) arising on the site shall be collected and removed from the site via a suitable and properly designed temporary drainage system.

Air Quality Control

Vehicles and machinery are be maintained regularly so that emissions conform to national and state ambient air quality (AAQ) standards. Periodic checks are undertaken, and remedial measures, including replacement, are carried out if required. Construction plants and equipment are maintained and operated so that recognized international standards for emissions are met.  Based on the emission factors for parameters such as SPM, sulfur dioxide, and nitrogen dioxide, the pollution load is calculated and regularly monitored. Construction sites are watered down to suppress dust during handling of excavation soil and debris and during demolition. Water sprinkling, hoardings, dust screens, and so on, are used. Emissions are controlled during transportation as well.

IDEAS AND THOUGHT PROCESS

A common problem encountered on different corridors was lack of environmental awareness among engineers and managers of DMRC who were involved in day-to-day construction activities. This was solved through regular environmental training programs.

The major concerns during the construction stage were poor housekeeping by the contractors and unauthorized use of the easily available natural resources and other available infrastructure such as roads and water resources. This could result in degradation of ambient air quality, water resources, and the land environment around the construction sites and the workers’ camp. Improper management of earthwork and bridge construction activities would disrupt the natural drainage and increase soil erosion.

Environment management programs and the planning and designing of the alignment and structures have been mitigating negative impacts. Most of the work on the ground is undertaken by consortia of contractors; hence, the most effective means of operation control during construction to achieve minimal environmental degradation has been adequate provision of environmental clauses in work contracts and efficient contract management. For instance, stringent guidelines were established for environmental management, safety, housekeeping, and traffic control in the contracts. The project implementation unit records an end-of-construction mitigation checklist to monitor the implementation of the mitigation actions before releasing the final payment for any work contract.

NEXT STEPS AND DISCUSSION
The lessons learned in the execution of Phase 1 of the project are being utilized and implemented in Phase 2. For instance, implementation of rainwater harvesting in the depot is informed by the experience in Phase 1. During the construction of Phase 1, a need for a water treatment plant was felt because of waste of untreated water; this issue has been taken up in Phase 2. DMRC highlights its commitment to enhance green cover in its environmental policy; it has made provisions for developing green cover in some stations in Phase 2 apart from the compensatory afforestation that has been undertaken. A common recycling plant for all construction waste, steel, and scrap is another green initiative. DMRC reduced the amount of cement required for making concrete and replaced it with fly ash. For instance, during the construction of the underground line from Kashmiri Gate to Central Secretariat, 30% of the cement was replaced with fly ash. Through design alterations such as reducing the size of metallic couplings in the underground section, DMRC claims to have reduced consumption of steel by 5,000 metric tons. Most of these environment friendly practices are proposed to be or are implemented on a small scale initially, to be increased and continually improved in the next phases.

THE ROAD AHEAD

Delhi Metro is the first railway project in the world to be registered by the United Nations Framework Convention on Climate Change (UNFCCC) under the Clean Development Mechanism (CDM), which will enable it to claim carbon credits. The certification report was produced by the Germany-based validation organization TUV NORD on February 22, 2009. That organization conducted an audit on behalf of the UNFCCC and found that DMRC prevented the emission of 90,004 tons of carbon dioxide from 2004 to 2007 by adopting regenerative braking systems in Delhi Metro trains. Certified emissions reductions (CERs) during the construction phase could be envisaged for future phases with environmentally friendly practices. Green Metro Stations is yet another initiative being undertaken in consultation with the Energy and Resources Institute (TERI) for establishing environmentally friendly techniques for energy consumption and preservation. The design would utilize climatic factors such as wind loads, use of solar energy, and air movement patterns; utilize natural light; recycle wastewater; harvest rainwater; and utilize minimal water during construction.

COMMENT ON THE WIDER APPLICABILITY OF RESULTS

According to a survey by the Central Road Research Institute, India (January–July 2009), the entire cost of Delhi Metro’s Phase 1 will be recovered by 2011 if the environmental and social benefits of the project are measured in terms of the economic rate of return. Experience with and expertise in rolling out environmentally friendly construction practices are being utilized by other metro projects in several other corridors across the country. Delhi Metro is a trendsetter for upcoming metros in Hyderabad, Kochi, Pune, and Bangalore and has drawn interest internationally. The environmental management initiatives undertaken during the construction and operation phases of the Delhi Metro rail project have become examples for replication. DMRC recently received its first international consultancy assignment for special assistance on a project implementation study for the Jakarta Mass Rapid Transit system in Indonesia.

NOTE:  This case study is made possible with the kind co-operation and insightful inputs from Mr. S.A Verma, Deputy Chief Environmental Officer and Mr. Mangu Singh, Director-Works of Delhi Metro Rail Corporation. This case study is representative of DMRC’s issues and efforts towards environmental management during construction stage. Due to vast expanse and nature of project detailed description is beyond the scope of this case study.
Reference
Environmental Impact Assessment for Phase II Corridors of Delhi Metro, August 2005, RITES Ltd.

The purpose of this study is to determine whether air instead of water cooling of a coal-fired boiler steam condenser is a desirable option in cases in which the boiler must be sited remote from its source of fuel. For a coal-fired power plant, for example, it is not uncommon to locate the plant a considerable distance from the coal mine and transport the coal by rail to the plant. This may be necessary to obtain an acceptable supply of water that is suited to the needs of the boiler, for steam production, and for condensation of the steam turbine effluent. When water is used for steam condensation and water availability is limited, it is common practice to discharge the condenser cooling water effluent to a cooling tower for reuse as a cooling medium in the condenser. Air cooling might be advantageous for use in such cases because a cooling tower could be eliminated, as would the cost of transporting the coal from the mine to the plant site. However, the calculations provided in this document indicate that the operating cost for air cooling does not appear to be competitive with that for water cooling even if the distance from mine to plant is, say, 500 miles. Locating a plant much farther than this distance from the fuel supply source to obtain an acceptable supply of cooling water appears impractical, although economics would be the determining factor. However, generating steam at very high pressure, at or above the critical point, appears to offer greater profitability than generating steam at much lower pressures, so that fuel transportation costs would have a lesser impact on profitability. Therefore, greater flexibility would be allowable in regard to the location of the plant (see Table 1).

Design of an Air-Cooled Steam Condenser

Figure 1 shows a drawing of an air-cooled steam condenser that is to be used as a model for comparing investment and operating cost for two types of condensers, one air-cooled and the other water-cooled. Note that the drawing shows a single condenser but that two condensers operating in parallel are required. A description of the numbered items in the figure follows:

1. 10 rows of vertical tubes, item 1
2. Each tube 2 inches in outside diameter on 4-inch centers and 50 feet long, along  with an air inlet plenum, item 2
3. An air outlet plenum, item 3
4. A forced draft fan, item 4: a total of six such fans for each condenser is required
5. Steam turbine outlet steam flows, item 5
6. Cooling air outlet vent stacks, item 6
7. Cooling air inlets, item 7;
8. Condensate outlets, item 8
9. Effective tube length of 50 feet, item 9
10. 6 repeating sections of condenser each 78.5 feet in length (item 10), for a total length of 471 feet
11. Air inlet plenum with a width of 12 feet (item 11), with this width resulting in a flow variation among all tubes of not more than 10%
12. Tube sheet width of 3.3 feet, item 12
13. Air outlet plenum, outlet plenum width 12 feet, item 13
14. Steam inlet plenum, item 14
15. condensate outlet plenum, item 15

The air-cooled condenser, uses cooling air entering at 70 F and leaving at 100 F, with steam effluent from the turbine entering and leaving the condenser at various temperatures and pressures, depending on boiler inlet and outlet temperatures and pressures. The steam turbine is to be used in conjunction with a generator with an output whose magnitude is discussed in later sections and in the Discussion.

Air-Cooled Condenser Operating Conditions

The air-cooled condenser design used in determining the performance of the condenser, boiler, steam generator, and steam turbine–generator system will be based on the dimensional and design data shown in Figure 1, and a total condenser heat duty of 5700 million BTU/hour, with that heat duty used for all the operational cases considered in this article. For the water-cooled condenser cases, it became obvious that a water-cooled condenser would be very much smaller than an air-cooled one and also less critical in terms of the impact it might have on the cost study. Hence, performance and cost data were determined from estimated heat transfer coefficients, but firm heat duty requirements and mean temperature differences were used, with appropriate cost data being obtained from Reference 1. The same thing was done in the case of air cooling, but detailed calculations had to be made to determine the effects of items such as air side pressure drop and fan horsepower, which had a very large impact on operating and investment cost. Thus, pressure drop and fan horsepower were calculated by using the following equations:

Pd = ((Cd)(Vo)²/(Sp.vol)(64.4))((Dt)(Lt)/(c-c)(Lt)(144))(Nt)  (Reference 2)
HP = ((Pd)(144)(Sp.vol))((Wair)/(60)(33000)(Ef))
Cd = Drag coefficient = 1.0, unitless
where Cd = drag coefficient; Vo = maximum air velocity between tubes, 100 ft/sec; Pd = pressure drop, lb/sq inch; Sp.vol = average specific volume of air, cubic feet/lb; Dt = outside tube diameter, feet; Lt = tube length, feet.; c-c = center to center spacing of tubes, feet; Nt= number of tube rows in direction of flow; HP = fan horsepower; Wair = air flow, lb/hr; Ef = fractional air efficiency.

Pd = ((Cd)(Vo)2/(Sp.vol)(64.4))((Dt)(Lt)/(c-c)(Lt)(144))(Nt)  (Reference 2)
HP = ((Pd)(144)(Sp.vol))((Wair)/(60)(33000)(Ef))
Cd = Drag coefficient = 1.0, unitless
where Cd = drag coefficient;
Vo = maximum air velocity between tubes, 100 ft/sec;
Pd = pressure drop, lb/sqinch;
Sp.vol = average specific volume of air, cubic feet/lb;
Dt = outside tube diameter, feet;
Lt = tube length, feet.;
c-c = center to center spacing of tubes, feet;
Nt= number of tube rows in direction of flow;
HP = fan horsepower;
Wair = air flow, lb/hr;
Ef = fractional air efficiency.

Additionally, the following calculated data are applicable:
Cooling air flow = 633 million lb/hr
Average Sp.vol of cooling air = 13.4 cubic feet/lb
Cooling air Pd = 0.39 lb/sq in = 10.9 inches water
Fan HP = 343,000
Overall heat transfer coefficient = 23.7 BTU/hr-sq ft-deg F based on inside coefficient of 100 and outside coefficient of 31
Cooling air temperature in/out, deg F = 70/100
Vo = Maximum air velocity between tubes = 100 ft/sec
Area of tube plane perpendicular to inlet air flow = 23,680 sq ft for each of 2 condensers
Free area between tubes = 50% of area based on distance between tube centerlines
Total number of tubes = 14,000
where ho = ((0.133)(cp)((Wa)/(Af))0.6))/(Dt)0.4 (Reference 3);
ho = outside heat transfer coefficient, BTU/hr-sq f.-degF;
cp = average air specific heat, BTU/lb, deg. F;
Wa = air flow perpendicular to plane of tubes, lb/hr;
Af = free area between tubes, sq ft;
Dt = outside tube diameter, ft.

Boiler Performance and Electric Power Production

Electric power production is determined from the steam enthalpy difference from inlet to outlet of the steam turbine resulting from isentropic expansion from inlet temperature and  pressure to outlet temperature and pressure at the saturation point of the steam. The condenser heat duty is equated to the unknown mass flow rate of steam multiplied  by the enthalpy difference between saturated steam and  condensed steam at the same  temperature and pressure. The steam flow thus calculated is multiplied by the enthalpy difference between the temperature at the boiler outlet, which is equal to the temperature entering the turbine inlet and the enthalpy of the condensate leaving the condenser. The result is the boiler heat duty. To obtain the mass flow rate of fuel necessary to satisfy the boiler heat duty requirement, the heat duty is equated to the mass  flow rate of fuel, which is assumed to consist of carbon, multiplied by 12,490, allowing the mass flow rate of carbon fuel to be determined. The factor 12,490 is the result of subtracting the heat content of the flue gas, exiting the boiler at an assumed temperature of 400 F, from the lower heating value of carbon, which is equal to 14,000 BTU/pound. The heat  content of the exiting flue gas is based on firing the fuel with 20% excess air. Since the  actual fuel is assumed to contain 10% noncombustible ash, to obtain the mass flow rate of coal, the calculated mass flow rate of carbon is divided by 0.9. The heat liberated by the combustion of coal, however, is the mass flow rate of carbon multiplied by the heating value of carbon, which is equal to 14,000 BTU/pound.

The overall thermal efficiency of the boiler-condenser-turbine–generator system is calculable and is found to be equal to the turbine generator power output divided by the total heat liberation, both expressed in BTU/hour.

Discussion

A total of four cases have been investigated:

• Case 1 provides data for an air-cooled condenser and a turbine inlet pressure and temperature of 1000 PSI and 1000 F, respectively
• Case 2 provides data for a water-cooled condenser and a turbine inlet pressure and temperature of 1000 PSI and 1000 F, respectively
• Case 3 provides data for an air-cooled condenser and a turbine inlet pressure and temperature of 3200 PSI and 1200 F, respectively
• Case 4 provides data for a water-cooled condenser and a turbine inlet pressure an temperature of 3200 PSI and 1200 F, respectively

A comparison of these cases indicates that overall thermal efficiency using water-cooled steam condensation is almost 5% greater than that for air-cooled steam  condensation. The bottom line:  water-cooled condensation results in increased earnings and lower investment cost compared with air-cooled condensation (see Table 1).

_

References
1. Aries, R. S., and Newton, R. D. Chemical Engineering Cost Estimation. New York: McGraw-Hill, 1945.
2. Binder, R. C. Fluid Mechanics, 4th ed. Englewood Cliffs, NJ: Prentice-Hall, 1962.
3. McAdams, W. H. Heat Transmission, 3rd ed. New York: McGraw-Hill, 1954.

Getting engineers to switch tools or change their work habits is never an easy task. Management may mandate a move to a particular piece of software or make modifications to the engineering workflow, but that top-down approach often is met with resistance, jeopardizing the overall product development goals.

Graco, which delivers systems and technology for a wide range of fluid-handling applications, has overhauled its design practices significantly, moving away from a pure trial-and-error design process and embracing simulation—specifically, computational fluid dynamics (CFD)—far earlier in the cycle. Incorporating CFD into the early design stage has helped Graco hit the mark on a number of fronts. The company has been able to optimize its designs and create more repeatable and predicable engineering results. The changes also have led to significant achievements on the product front. Specifically, Graco was able to deliver a state-of-the-art plural component spray gun in two-thirds the time of its traditional cycles despite the fact it was a product design in which the company lacked prior engineering expertise.

The move to treat CFD simulation as an integral part of early design work instead of a late-stage specialty phase did not unfold from the top. There was no formal corporate mandate and no concerted effort by engineering management to enact changes to existing engineering workflows. Instead, the transformation evolved slowly over the course of the last six or seven years, led by the success of a single engineering team that went on to promote the practice and the results to the rest of the organization. What began as a technology experiment and later an informal exchange between a couple of colleagues has blossomed into a grassroots campaign to promote the use of CFD to other Graco divisions and product groups. This gradually introduced compelling changes to the company’s product development practices. The upside from this kind of slow and organic approach is that there has been automatic buy-in from the engineering ranks as more individuals and projects groups decide to adopt CFD as part of their processes.

Trial-and-Error Design

Traditionally, CFD did not have a starring role in the product development process. Years back, the company had a single license for a high-end CFD tool that was used by one engineer, who was charged with running simulations for the different groups within the company on an as-needed basis. The complex models would take days, if not weeks, to set up and run—a lag time that discouraged engineers from employing CFD as part of their efforts. When that individual engineer left Graco, the company was left with a void, having no one adequately trained in the specific tool and CFD discipline to pick up the task.

As a result, the bulk of the development projects remained a trial-and-error process that went much like this: An engineer would start with a benchmark that usually was based on scaling up the original design. After building and testing a physical prototype, the team would identify performance problems, take a guess at the reason for the problem, address it with a new design, and start the prototype and test cycle anew. This process would continue through multiple designs and scores of prototypes until a satisfactory but not optimized design was found.

Optimizing designs with the trial-and-error method was typically not practical for a number of reasons. First, it was far too time-consuming and costly to build a prototype of each ensuing design iteration. It also was next to impossible to predict flow patterns, which are an integral part of the plural-component spray gun products. The spray guns are designed to apply materials, such as polyurethane foam insulation and polyurea, that have to be mixed just before spraying. The performance of the spray guns is predicated on how thoroughly the unit mixes the two components that constitute polyurethane foam: the resin and the catalyst. Controlling the motion of the spray is another critical design element since it is key to delivering the desired pattern shape on the surface to which the substance is applied.

When a team was charged in early 2003 with creating a new kind of plural-component spray gun, it became clear that the trial-and-error process was no longer practical. The specifications called for the gun to deliver round spray patterns with a diameter 50% greater than the standard. Simply scaling up the mix chamber from existing designs would not deliver optimal performance because the nature of fluid flow changes substantially when the scale of the design is modified. That problem prompted the team to revisit CFD technology as a means to simulate the fluid flow inside the gun so that the team could experiment with various iterations and optimize a design well before building a costly physical prototype.

Using FloEFD from Mentor Graphics’ Mechanical Analysis Division, the team was able to home in on an optimized design in less than four months, a third of the time it would have taken with the old trial-and-error approach. The resulting product, the Graco Fusion Air Purge Spray Gun, was a resounding success, helping the company garner more than a 30% market share in just two years despite the fact that it was Graco’s first entry in this category.

Lessons Learned

Word of the Fusion team’s success with CFD spread quickly. Engineers throughout the different divisions began to reach out to the Fusion team to learn about the role of CFD and specifically to get a jump on using the Mentor FloEFD tool. The technology became an agenda item at interdivisional engineering meetings, in which the divisions regularly share information and provide updates on project status. The word-of-mouth campaign continued over the last few years, and as a result, CFD is now deployed in Graco’s three divisions by multiple engineers and designers, not just one or two fluid dynamics experts.

The choice of tool was critical to CFD’s expanded use. Mentor FloEFD works within commonly used computer-aided design systems so that engineers can access the functionality without having to master a new discipline or learn another complex design program. The Fusion team also played a key role in introducing the technology to others. As word spread, the team did its part to acquaint engineers with CFD technology and provide basic training on the FloEFD product. Because of the grassroots culture, the responsibility for serving as the CFD champion did not last long. As individual engineers and groups came up to speed on CFD, they took on that role, creating a broader base of proponents to provide mentoring and support and underscore the value of infusing CFD into the early design phase.

There is still work to be done to promote CFD, and eventually engineering management may opt to take a more active role. Nevertheless, there is no denying that CFD has made consistent inroads in the Graco engineering culture and significantly altered the way the firm designs and builds products.

As the supply of fossil fuels decreases, it is possible that future stationary or mobile energy systems will use hydrogen fuel cells. This article outlines some rules of thumb for fuel cells and describes the basic calculations required to size a fuel cell appropriately and determine hydrogen fuel requirements.

Fuel Cell Reactions

Many types of fuel cells combine hydrogen with oxygen to produce DC electricity. The by-products of the reaction are water vapor and heat. The proton exchange membrane fuel cell (PEMFC) reactions are as follows:

Anode:     H2 → 2H+ + 2e-
Cathode:  ½O2 + 2H+ + 2e- → H2O
Overall:    H2 + ½O2 → H2O

where H+ denotes hydrogen ions (protons) and e- denotes electrons. Note that two electrons are produced for each hydrogen molecule.

Determining the Number of Cells

Vehicle applications would require approximately P = 100 kW (132 horsepower [hp]) of peak power to supply an electric motor at a total voltage V = 300 V. Thus, the current I in amperes would be given by the power divided by the voltage. Thus,

I = P/V = 100000 W/300 V = 333 A

A typical rule of thumb for the voltage of a single-cell fuel cell Vc is to operate at about 0.7 V. As cells are stacked together within a larger fuel cell, the voltage is additive. Thus, the number of cells required N is given by the total voltage divided by cell voltage, such that:

N = V/Vc = 300 / 0.7 = 429 cells

Determining the Cell Size

Fuel cell performance is described by a polarization plot, as shown below

This plot relates the cell voltage Vc to current density i. Since for this application the cell voltage is known, the current density can be read from the plot as i = 950 mA/cm². To produce 333 A of current, the cell cross-sectional area A required is equal to the total current I divided by the current density. Therefore,

A = I/i = 333 A / (0.950 A/cm²) = 350 cm²

Determining the Hydrogen Requirements

The required hydrogen molar flow rate (in mol/s) is given by the following relationship: ξH2 = IN/zF, where z is the number of electrons produced per mole of fuel and F is Faraday’s constant, given by 96485 Coulombs of charge per mole of electrons. Note that in this expression, z is 2 since 1 mol of H2 produces 2 mol of H+ ions and 2 mol of electrons. With this in mind, we obtain:

Determining the Heat Production

The fuel cell stack heat production Q in W is given by Q = P(1.25/Vc-1) Note that in this formula, 1.25 is the maximum theoretical voltage if all the thermal energy in the hydrogen is converted into electricity. Thus,

This heat can be removed with the vehicle radiator.

Fuel Economy: A Try-It-Yourself Final Note

Note that at a constant highway speed of 88 km/hour, the power requirement is about 25 kW = 25000 W. A trial-and-error solution (or a plot of stack power P in W as a function of the stack current I in A) shows that the fuel cell stack would operate at I = 62 A and V = 403 V, with a cell voltage Vc = 0.94 V, a current density i = 177 mA/cm², and a hydrogen consumption rate of 0.138 mol/s = 0.276 g/s = 0.992 kg/hour. Thus, the fuel cell vehicle can obtain about 88 km = 60 miles on 1 kg of hydrogen.

Note that in this final example, an electric DC/DC voltage converter would be needed to change the fuel cell output to the 300 V required for the electric motor.

Among the general public, interest in alternative fuels tends to rise and fall with each tick in the price of traditional gasoline. However, the growing importance of energy security and environmental protection means that alternative fuels are here to stay. The real question nowadays is which types of alternative fuels will have the greatest staying power.

On that score, biofuels derived from algae have a lot going for them. Algae are inherently renewable, require little energy to produce compared with other bio feedstocks, and do not take agricultural land out of food production. When grown under the proper conditions, algae can produce large quantities of oil that can be harvested and then converted into a variety of biofuels, including green diesel and a even a bio-based jet fuel.

Fuel from algae also promises significant environmental benefits aside from the role of algae as a fuel source. For example, the oil harvested from algae shows promise as a feedstock for polymers and industrial chemicals currently derived from petroleum. The systems that grow algae for harvest, or “bioreactors,” also can be used to sequester the carbon dioxide generated by nearby power plants or factories. In these applications, the algae plant would use the carbon dioxide generated by a colocated plant or factory as a nutrient source, preventing that greenhouse gas from reaching the atmosphere.

If algae makes such a great feedstock, why has its production so far been relegated to small-scale research and other precommercial projects? It turns out that growing large quantities of algae reliably is not easy, in part because it requires a synthesis of biological and engineering expertise.

Until recently, too many algae-to-fuel research efforts overemphasized the biology and neglected the engineering. These systems have been designed to support one or just a few specific algae species, and some of these systems are not designed to scale out of the lab.

Renewed World Energies took a different tack by engineering a bioreactor that is flexible enough to support many different varieties of algae: 16 and counting in our tests. It is also easily scalable from a self-contained research system that fits on a flatbed truck to commercial production facilities that could span acres.

Starting with the engineering was a no-brainer given the background of our technical staff. These engineers cut their teeth not in the lab but in the chemical process, petroleum, and pulp-and-paper industries. Over the years, they have been responsible for billions of dollars of large-scale capital projects. Also, we approached the problems of algae growth, harvesting, and processing just as we would approach any large-scale chemical engineering project: with attention to automation, mechanical design, system performance, and cost constraints.

AUTOMATED BIOREACTOR

Bioreactor Design - Click to Enlarge

After six years of development work, RWE came up with a patent-pending bioreactor design that consists of vertical “ponds,” automated process controls, and a harvesting system.

The vertical pond system is a modular closed container optimized for algae growth. Each of these panel-like modules measures 4 feet wide by 6 feet high by 3 inches thick and is made from thermoformed high-density polyethylene (HDPE). We spent many engineering hours fine-tuning the internal flow path geometry and material of the panels so that they would have the water flow and light transmission characteristics required for maximum algae growth.

The vertical panels are held in a rack that we designed to handle the heavy loads; full panels weigh 4,000 pounds. The rack also separates individual panels to allow light transmission, and it facilitates pond installation thanks to integrated quick-connect piping headers.

The automated process controller governs every aspect of algae growth and harvesting  with minimal operator input requirements. The system uses a collection of sensors, some on-line and some off-line, to monitor the algae-growth variables, which include flow rate, temperature, pH, nutrient levels, dissolved oxygen, and turbidity. Proprietary control algorithms make adjustments to these growth variables by adjusting a series of pumps and valves that circulate water, C02, and other nutrients inside the chambers of the pond.

When harvest time comes, the controller actuates pumps and valves that send the oil-rich algae to a prescreening station that reduces moisture to approximately 20 percent. The semiwet algae is pumped to a holding tank for pickup or piped to a final screening, where it can be dried further if necessary. The oil then goes on to a processing plant where it can be converted into various types of fuels or chemicals. For example, a variant of the well-known Fischer–Tropsch process can transform the oil into biodiesel.

Because automation is such an important part of making the system function reliably and adjust to different growing conditions, a lot of development time was spent on the controller design. After looking at control products from a handful of the major vendors, we went with a control architecture based on Siemens products: an S7-300 controller programmed with SIMATIC process control system software. The S7-300 controller talks to Siemens Micromaster variable-speed drives, which in turn control the stainless-steel impeller pumps that move fluids through the system. One reason we went with Siemens is that we able to integrate its controller and drives seamlessly, which was important from both development and operational standpoints.

Another important aspect of the Siemens architecture is that it supports wireless control, which gave RWE a big advantage in terms of scalability. With control signals going over an industrial wireless network, installations spread over acres of real estate can avoid the expense of wiring each pond back to a control station.

ENGINEERING FOR COST AND PERFORMANCE

In developing our system, the chief goal was to come up not just with a system that grows algae but with a system that grows algae commercially, with all the cost constraints and performance goals that the term “commercial” implies.

Our efforts to contain costs can be seen throughout the system. The pond panels, for example, are produced in a high-volume manufacturing process (thermoforming) rather than with expensive low-volume methods. To take another example, we created a back-flushing system that uses our existing flow control components to remove algae that sticks to the interior walls of the pond. Other systems have used mechanical “wipers” that add complexity and cost.

In the automation system, the wireless capabilities promise tremendous cost savings as algae production covers more and more ground to reach commercial volumes. Consider our instrumentation strategy. Our system employs on-line sensors where needed but relies on less costly hand-held instrumentation for measurements that don’t have to be in real time. At the end of the day, our efforts paid off. Development costs for this  commercial system for roughly $4 million; in comparison, some noncommercial systems cost two or three times as much.

Still other design decisions were made for the sake of performance, which can be defined in terms of yields, ease of operation, and scalability. In the mechanical system, for example, our engineers picked closed impeller pumps that protect algae from shear that can destroy their cell structure and lower yields. The pond system is also inherently scalable and easy to install because of its modularity and quick-connect features: Want more algae, simply connect more ponds.

The first use for our algae bioreactor is at our own facility in South Carolina. Currently in its pilot phase on five acres, our algae system ultimately will grow to ten acres or more and feed a direct gasification plant capable of producing more than 500,000 gallons of green diesel and 25,000 gallons of green gas per year. Working with technology partners, RWE plans to supply algae oil derivatives for other biofuels, bioplastic feedstocks, and industrial chemicals for use in pulp and paper production. Beyond our own bioreactor use, RWE is set up to supply bioreactor and process technology to users, both large- and small-scale, when they want to strike algae oil of their own.

Renewable alternative energy sources are becoming more economically viable, partly as a result of concerns about the effect of CO2 from fossil fuel on global warming and the rising cost of oil and natural gas. Biogas from the anaerobic digestion of organic waste from livestock operations and food processing has long been used as a source of fuel in developing countries such as China and India.

New advances in aerobic digesters and biogas cleaning technology over the last few years have led countries such as Germany to forecast that 17% of their energy requirements for natural gas will be supplied from biogas by the year 2020.

DESCRIPTION OF THE CHALLENGE

Biogas from anaerobic digesters contains approximately 65% methane; 30% CO2, H2O, and N2; and up to 1% H2S.  H2S converts to sulfuric acid with moisture, and this is very corrosive to biogas processing equipment.  New advances in H2S control technologies have made it possible to remove H2S from biogas so that it can be used as clean fuel.  One such technology is the next generation of venturi scrubbers developed by ALTECH Technology Systems with the patented System REITHER venturi scrubber.

Based on field trials, theoretical calculations, and full-scale installations, our design incorporates a venturi scrubber with a second-stage nozzle scrubber, using NaOH to remove high levels of H2S from biogas with over 99% efficiency.  This design limits the absorption of NaOH by CO2 by using the short residence time of the biogas in the venturi, which favors the reaction with H2S over CO2.  This greatly reduces NaOH consumption and the associated costs common in packed tower scrubber technology.

DESIGN AND PROCESS

System REITHER is a wet scrubbing process for air pollution control that uses a patented venturi throat design for the control of fine dusts, mists, aerosols, and gases. This new, patented advance in venturi scrubbing achieves removal efficiencies that usually are higher than 99%.

New advances in throat design have led to significant improvements in removal efficiencies, the ability to respond to variability in flow, and the ability to remove gases and submicron particles and aerosols.

Figure 1. Venturi Throat Design

The principle of this patented design is illustrated in Figure 1, in which it is shown that the contaminated airstream flows through the duct and is forced by two outside cylinders into the middle region.  Through the addition of a third cylindrical displacer on a manually adjustable shaft, a double split is formed, creating two venturi throats.  The vertical movement of the displacer can vary the throat to the optimum width for maximum efficiency even during variations in flow.

The scrubbing liquid is introduced through the main spray headers positioned over the venturi throat.  These nozzles have relatively large openings, and this introduces scrubbing fluid to the venturi throat.  The design is based on maintaining an air velocity or speed through the throat of 100 meters per second, which shears the water droplets and creates atomization.  This “shear” velocity breaks the liquid aerosols apart or shears them into a very fine mist, maximizing the opportunity for the scrubbing liquid to collide with submicron particulates and/or gases.  Because of the intimate contact between the airstream and the scrubbing liquid, the use of an additive such as sodium hydroxide or hydrogen peroxide can achieve an instantaneous catalytic reaction with gases such as hydrogen sulfide and other associated compounds.

After the venturi, the airstream enters a secondary nozzle scrubber to provide additional retention time and scrubbing fluid for high volumes of H2S.  As the reacted scrubbing mist enters, the heavier specific gravity pulls the captured gases down into the reservoir. The clean biogas is discharged at the top. Although there are a number of demister designs, the cyclonic demister is the best choice for this situation because there is no chance for plugging and reduced performance.

This project focuses on the design and operation of a scrubber to remove H2S from a municipal sewage pumping station and from biogas generated from covered anaerobic wastewater lagoons at a beef-processing plant.

FIELD TRIALS

H2S Control at a Municipal Wastewater Pumping Station in Ontario, Canada

A municipal wastewater pumping station in a residential location was receiving numerous complaints about odors.  It was situated downstream from a chicken-processing facility, and wastewater from the cleaning cycle was going anaerobic during low flows at night.  H2S was the main odor component, with levels up to 200 ppm recorded over the wet well channels.

Altech conducted a pilot plant demonstration using System REITHER technology to control hydrogen sulfide and other odorous compounds.  Low concentrations of sodium hydroxide and hydrogen peroxide were used with water to remove hydrogen sulfide; the chemical reaction is as follows:

4H2O2 + H2S = H2SO4 + 4H2O

2NaOH + H2SO4 = Na2SO4 + 2H2O

Chemical scrubbers using packed tower technology have been used traditionally for this application.  This technology typically uses a two-stage scrubber system to produce the efficiencies needed to remove more than 99% of the hydrogen sulfide that is generated.

This odor control design uses high-efficiency venturi technology to remove more than 99% of the hydrogen sulfide in a single-stage system.   High-velocity airflows in the venturi throat atomize the scrubbing fluid to create a large scrubbing fluid surface area that forces contact with contaminates.  Figure 2 shows the results of the pilot demonstration in regard to hydrogen sulfide removal.

Figure 2. Results of the Pilot Demonstration

One of the challenges of this study was to determine the effectiveness of both sodium hydroxide and hydrogen peroxide as additives to the scrubbing liquid.  Hydrogen peroxide is a strong oxidation agent, whereas sodium hydroxide is used to convert the H2S catalytically to the more inert sodium sulfate.  Both compounds were used in low percentages that ranged from 0.5% to 1.5%.  Both compounds were effective; however, hydrogen peroxide required a slightly higher concentration to perform effectively.  Sodium hydroxide appeared to react effectively with the H2S as a catalyst to reduce the compound to sodium sulfate.  The inlet and outlet gas was analyzed by real-time H2S monitors that could demonstrate the results of the reaction immediately.  Also, the scrubbing liquid led to a buildup of small solid particles of a consistent size that would be indicative of the deposits of sodium sulfate.  The conclusion, then, was to use sodium sulfate as the scrubbing system additive only at a percentage of 0.5%.

Major Beef-Processing Facility in the Midwestern United States: H2S from Biogas Generated from Anaerobic Lagoons

A pilot study using System REITHER technology to remove H2S from biogas at a beef-processing plant was conducted on February 10, 2009.  Hydrogen sulfide levels were around 4,600 ppm from biogas generated in covered anaerobic wastewater treatment lagoons.  Biogas was being treated by using iron sponge technology, which was not designed to handle the H2S loading.  A breakthrough was occurring every 30 days of operation.

System REITHER technology demonstrated 90% removal of H2S using a solution of 1% NaOH with water as the scrubbing fluid.  NaOH outperformed hydrogen peroxide, sodium hypochlorite, chlorine dioxide, and ferric chloride as the chemical additive to remove H2S at these levels.  However, based on these levels, the sodium hydroxide was consumed very quickly.

It was noted that as the pH of the scrubbing fluid dropped, removal efficiencies of H2S were reduced as the NaOH was consumed.  It was clear that the sodium hydroxide was very effective at treating the H2S; however, at these concentrations, the pH of the scrubbing fluid could drop from 13 to 1 in 20 minutes.  Clearly, the treatment efficiency decreased accordingly.  The challenge, then, was to achieve reliable high treatment efficiency consistently on an ongoing basis.

The project team designed a dosing system that would measure the pH in the reservoir of the scrubber system and continually injected sodium hydroxide to maintain a high pH.  This approach optimizes the consumption of sodium hydroxide while ensuring high treatment performance.  Table 1 shows the trial results.

Table 1: Trial Results Showing H2S Removal from Biogas Generated in Anaerobic Lagoons

SUMMARY

Chemical air scrubbers have been shown to be very effective by chemically treating odorous gases such as hydrogen sulfide and ammonia.  Although traditional packed tower chemical scrubbers have been shown to be effective in controlling some odors, there are drawbacks such as a large footprint, packing media that have to be replaced over time, and, in the case of biogas, a longer retention time that results in high caustic consumption created by absorption by the high percentage of CO2.

Venturi air scrubbers traditionally have been used to control airborne particulates and aerosols from contaminated air.  The System REITHER advanced design has been demonstrated to be very effective in controlling gases such as hydrogen sulfide that chemically react with additives in scrubbing fluid together with fine airborne particulates.

Based on data from the study, sodium hydroxide was the most effective scrubber addition and had good treatment performance at low percentages in the scrubber liquid.  Consumption was governed by the concentration of H2S, which can be highly variable in biogas.  In the case of the beef processing facility, it was consistently 4,600 ppm, which is extremely high.

The benefits of this technology include the following:

• Scrubs many gases and airborne particulate contaminates simultaneously.
• Small footprint and overall size compared with other technologies.
• Simple compact design with no moving parts and low maintenance requirements.
• No media to replace; no channeling or breakthrough.
• High-efficiency technology can achieve >99% removal of odorous gases and particulates in a single-stage system,
• Handles variable airflows with patented adjustable venturi throat.
• Scrubbing fluid can be recirculated without nozzle clogging because of the unique design.

REFERENCES

Table 1:  H. J. Taback, G. C. Quartucy, and R. J. Goldstick, eds. Alkaline and Stretford Scrubbing Tests for H2S Removal From In-Situ Oil Shale Retort Offgas. KVB, Inc., Engineering and Research Division, Irvine, CA, 1985.

The term CCHP (combined cooling, heating, and power) is used to describe all electrical power generation systems that utilize recoverable waste heat for space heating, cooling, and domestic hot water purposes.  The main difference between CCHP systems and the typical methods of electrical generation is the utilization of the waste heat rejected from the prime mover to satisfy the thermal demand of a facility. A schematic of a typical CCHP system is shown in Figure 1. The primary goal of c is to present a more attractive option than traditional power supply methods.

CCHP systems usually are operated by using two basic strategies: following the electric load (FEL) and following the thermal load (FTL).¹  However, in addition to the operation strategies, it is necessary to apply optimization criteria to guarantee the benefits of CCHP systems over conventional technologies.  The CCHP system operation strategy will dictate the loading and fuel consumption of the prime mover and thus the energy consumption profile of the CCHP system.

In the case of the FEL operation strategy, the prime mover is loaded to satisfy the electrical demand of the facility through the power generator unit.  The waste heat from the power generation unit then is recovered to satisfy the thermal load of the facility.  For this operational strategy, if the recovered thermal energy is not enough to handle the thermal load (cooling or heating) of the facility, additional heat has to be provided by the auxiliary boiler of the CCHP system.  For the FTL strategy, the prime mover is loaded so that the recovered waste heat will be adequate to supply the facility with the necessary thermal energy to satisfy the heating and cooling requirements. For this operational strategy the amount of electricity produced may or may not be sufficient to provide the electricity required by the building.  Therefore, if the electricity produced is not enough to handle the electrical load, additional electricity has to be imported from the grid.  In contrast, if the electricity produced is more than is required, the excess can be sold back to the grid.

The choice of a CCHP system strategy largely depends on the specific goal of the CCHP system operation.  Typically, analyses of CCHP systems are based on reduction of operational costs.  However, in addition to cost, CCHP systems can be optimized on the basis of different optimization criteria, such as primary energy savings and minimum environmental impact.²  Therefore, in addition to the operational strategies (FEL and FTL), optimization techniques have to be employed to guarantee the lowest cost of operation, reduction of the primary energy consumption (PEC), and/or reduction of carbon dioxide emissions (CDE).

PERFORMANCE OF CCHP SYSTEMS USING DIFFERENT OPTIMIZATION CRITERIA

A reference building was defined to illustrate the performance of CCHP systems under different operational strategies and optimization criteria.  The reference building, which is in Columbus, MS, is a small office with 465 m2 of floor area and a total consumption of electricity and natural gas of 50,942 kWh/year and 12,380 kWh/year, respectively.  With the building site energy consumption data, a comparison of the CCHP system performance with the reference case as well as the optimization of the CCHP system can be performed.

Figure 2 shows the variation of the PEC, the cost, and CDE with respect to the reference case for the two basic operation strategies.   (In all the figures, a negative number implies reduction and a positive number implies increase.)  Figure 2 demonstrates that the FTL strategy reduces the PEC by 4.8% whereas the FEL slightly increases it.   The FEL and FTL strategies decrease the CDE by 13.8% and 12.2%, respectively, while increasing the cost.  However, FTL increases the cost by only 1.5%, whereas FEL increases it by 12%.  In general, it can be seen that for this city, FTL provides better performance than FEL since it reduces the PEC and CDE with the minimum cost increase.  For the FTL strategy there is an excess of electricity of about 7,000 kWh/year that could be translated into an additional 14% of PEC savings.  The cost savings that could be obtained from the excess electricity have to be estimated for each specific location in terms of whether it is possible to sell it back to the utility companies.

The results presented in Figure 2 can be optimized to guarantee the lowest cost of operation, reduction of primary energy consumption, or reduction of carbon dioxide emissions.  Figure 3 illustrates the variation of the PEC, the cost, and the CDE obtained when the primary energy optimization criterion (PE-O) was applied.  It can be observed that FEL operating under the PE-O reduces PEC, cost, and CDE by 7%, 1.5%, and 13.4%, respectively.  The use of the PE-O for FEL is beneficial since it reduces PEC and cost that otherwise increase when the CCHP system is operated FEL without any optimization criterion.  Similarly, FTL operating under the PE-O reduces PEC, cost, and CDE by 7.5%, 3.7%, and 12%, respectively.  The use of the PE-O for FTL is also favorable since it produces higher reductions of PEC and especially cost, which increase when the CCHP system is operated FTL without any optimization criterion.  Another important issue is that when this optimization criterion is used, all the evaluated parameters (PEC, cost, and CDE) are reduced compared with the reference case for both operation strategies.

Figure 4 shows the variation of the PEC, cost, and CDE obtained when the operational cost optimization criterion (OC-O) was applied.  FEL operating under the OC-O reduces PEC, cost, and CDE by 5.5%, 3.0%, and 8.4%, respectively.  Similar to the PE-O criterion, the use of the OC-O for FEL is beneficial since it reduces PEC and cost.  The use of OC-O for FTL reduces the PEC, cost, and CDE by 7.0%, 4.4%, and 9.9%, respectively.  This optimization criterion is beneficial for the FTL strategy since it provides higher reductions of cost than does the CCHP system operated using the FTL strategy without any optimization.  Using this optimization criterion, all the evaluated parameters are reduced compared with the reference case for both operational strategies.  The CDE reduction obtained when cost is optimized is lower than the reduction obtained when primary energy is optimized.  In general, FTL shows better performance than FEL when cost is optimized.

Figure 5 shows the variation of the PEC, cost, and CDE obtained when the emission reduction optimization criterion (ER-O) was applied.  This figure shows that FEL operating under the ER-O reduces PEC and CDE by 5.7% and 14.8%, respectively, and increases the cost by 2.1%.  In addition, Figure 5 illustrates that FTL operating under the ER-O reduces PEC, cost, and CDE by 6.6%, 1.2%, and 12.9%, respectively.  Similar to the other two optimization criteria, the use of the ER-O is beneficial for FTL since it provides higher reductions of CDE, PEC, and especially cost.  It is important to point out that for FEL, the optimization of the emissions reduction is achieved at the expense of the cost.  This reflects the fact that optimizing one parameter may increase or decrease the other two.

Figures 3, 4, and 5 demonstrate that most of the optimization criteria yield better results than that obtained with a CCHP system operating FEL or FTL without any optimization.  In general, if CCHP systems increase the cost of operation, as long as energy savings and reduction of emissions are guaranteed, the implementation of these systems should be considered.

CONCLUSIONS

The performance of CCHP systems can be improved by using different optimization criteria, such as energy savings, operational cost reduction, and minimum environmental impact.  For the case presented here, it can be concluded that all the optimization criteria yield better results than does CCHP operating FEL or FTL without any optimization. The selection of the optimization criteria depends on the main goal of the CCHP system and has to be analyzed carefully to determine the effect on the other parameters.

REFERENCES

¹ Mago, P. J., Fumo, N., and Chamra, L. M. “Performance Analysis of CCHP and CHP Systems Operating Following the Thermal and Electric Load.” International Journal of Energy Research, 2009, Vol. 33, pp. 852–864.

² Mago, P. J., Chamra, L. M., and Hueffed, A. “A Review on Energy, Economical, and Environmental Benefits of the Use of CHP Systems for Small Commercial Buildings for the North American Climate.” International Journal of Energy Research, 2009, Vol. 33, pp. 1252–1265.

This article describes the performance of a novel vertical axis wind turbine (VAWT). The Zephyr VAWT has a patented stator cage that can increase the turbine’s performance through the creation of low-pressure vortices. The patented features of the turbine allow it to perform in both low-wind and high-turbulence conditions; however, a relatively low maximum efficiency is exhibited by the current prototype design. A problem arises when incoming air is diverted away from the convex sides of the rotors, reducing opposing forces to the direction of rotation; however, the solidity (blockage) is increased, reducing the overall flow through the turbine.

Figure 1: Geometrical variables of the Zephyr vertical axis wind turbine

Manufacturers of fluid machinery such as small wind turbines are interested in this because efficiency improvements often are needed to obtain more feasible designs for commercialization. This article uses dimensional analysis and numerical predictions to obtain a turbine-specific correlation for the ZVAWT. The correlation will predict the turbine’s power coefficient after changes to critical features of the VAWT and operating conditions, such as the rotor velocity and wind speed (see Figure 1). The new dimensionless correlation will provide a valuable design tool that can be extended to other types of turbines for the purpose of predicting performance over a range of operating conditions.

Solution Procedure by Buckingham Pi Dimensional Analysis

In regard to the Zephyr VAWT design, nine key variables are identified to represent the turbine power output (Ω ) for different stator geometries.  The variables are the rotor velocity (Φ), rotor radius (R), freestream velocity (V), air density (ρ), turbine height (H), turbine width (W), stator spacing (σ), and stator angle (θ). The power output depends on these variables as follows: F = f(r, V, R, H, W, s, q, W). The dimensions of these variables can be represented by the base dimensions of mass (M), length (L), and time (T), as follows: F ≡ M¹ ∙ L² ∙ T^-3, r ≡ M¹ ∙ L^-3 ∙ T⁰, V ≡ M⁰ ∙ L¹ ∙ T^-1, R ≡ M⁰ ∙ L¹ ∙ T⁰, H ≡ M⁰ ∙ L¹ ∙ T⁰, W ≡ M⁰ ∙ L¹ ∙ T⁰, s ≡ M⁰ ∙ L¹ ∙ T⁰, q ≡ M⁰ ∙ L⁰ ∙ T⁰, and W ≡ M⁰ ∙ L⁰ ∙ T^-1. From these nine variables and three dimensional units, the Buckingham pi theorem states that six dimensionless pi terms will be sufficient to represent and predict the performance of the turbine. The reference variables, ρ, , and R lead to the following three pi variables, as determined by the Buckingham pi theorem:

Combining these three terms yields the following power coefficient (Cp):

The fourth and fifth pi terms are additional terms for representing changes in the stator geometry:

The last pi term is represented in terms of R, Ω, and V. It is equivalent to the variable tip speed ratio (λ), a common dimensionless parameter for wind power analysis:

These terms are combined so that:

Which can be reduced to

where ø will be determined through numerical predictions with CFD (computational fluid dynamics). This expression will lead to correlations that provide useful insight into the turbine’s geometric characteristics. It also will provide key information for design and power output improvements.

Results and Discussion

The power correlation is developed from 16 numerically simulated geometrical configurations. Predicted values of C_p at varying magnitudes of П₄ are used for the dimensional analysis. Four power curves are generated to represent discrete values of θ, specifically 0.698, 1.57, 1.92, and 2.27 radians.

To collapse the four curves associated with each of the four cases into a single correlation, they are normalized in following  dimensionless plane:According to the function:where:

The normalization coefficient f(θ) can be represented as:where minimal variability is exhibited, compared with the numerical prediction (R² = 0.91).  The normalization coefficient g(θ) can be represented by:which shows minimal variability with the numerical prediction (R² = 0.98). After all power curves are collapsed onto a single normalized power curve, the general correlation becomes:where f(θ) and g(θ) are described by Equations  (9) and (10), respectively.

Additional numerical predictions have been obtained and compared with the correlation described by Equation (11). Figure 2 illustrates the ability of the model to predict results that lie outside the CFD simulated conditions. For example, three additional ZVAWT configurations are represented at θ = 2.09 radians and θ = 1.15 radians, with associated errors of 4.4%, 5.8%, and 2.9%, respectively. The correlation generated from the combination of a dimensional analysis and numerical simulations provides an excellent prediction of the turbine’s performance:

Figure 2: Illustration of the dimensionless power correlation

Conclusions

As a result of the development of a general correlation that predicts the ZVAWT’s performance, further design improvements can be undertaken without the need for time-consuming CFD predictions in each case. The correlation provides a useful design tool for adapting the turbine conditions and operating requirements specific to this drag-type VAWT. It becomes easier to predict quickly how changes to the VAWT’s design features will affect its performance with a reasonable degree of accuracy. The correlation also can be useful for developing an optimum turbine design while limiting the need for further CFD simulations and time-intensive mesh generation for each different turbine configuration.

It is often the case that the simpler the product, the greater the complexity surrounding its design. That is certainly true at Dana Holding Corp.’s Sealing Products Group, which manufactures top-to-bottom engine sealing systems for the automotive sector, including cylinder head covers, all kinds of gaskets, and valve stem seals. The division’s products are highly engineered and have to perform consistently over a protracted period in a dizzying array of unique environmental and system conditions. Because of that scenario, the process calls for extensive testing and verification of designs, yet the group could hardly be cost-effective and time-efficient if it relied exclusively on a build-and-test process involving physical prototypes.

With that in mind, the Sealing Products Group set out several years ago to transform its traditional processes and pursue an analysis-led design approach. Analysis-led design entailed standardizing on a well-developed, integrated computer-aided engineering (CAE) software portfolio and a set of engineering processes so that the team could design products properly up front, test them virtually to optimize performance, and cut back on the number of physical prototypes it had to build. Over time, the new design approach would help Sealing Products Group vastly reduce development costs, not to mention pushing product out the door faster.

The importance of an analysis-led design strategy becomes clear when one considers the competitive landscape the Sealing Products Group faces. Regulations for emissions and fuel and noise control are evolving continually and becoming more stringent, forcing a new set of requirements for the exhaust system along with the associated sealing components. Despite the increasing complexity of product requirements, the number of global players vying in this territory is on the rise. Thus, the analysis-led design transformation was viewed as a key survival strategy for differentiation, a path that would help the Sealing Products Group meet its goals of accelerating time to market and achieving consistent high-quality performance across its broad spectrum of products.

Despite the technical limitations of both the hardware and the CAE software when the journey began nearly a decade ago, the team was confident that it had embarked on the right course. Because its products are all about forming, contact, and assembly, they are highly nonlinear, making it difficult to predict stress and strain performance by using traditional prototyping techniques or even to track the results with manual tools such as spreadsheets. In terms of durability, one also is looking at extremely long testing setups and cycles. It was not uncommon to put a design through 1,000 hours of dyno testing only to find a problem when the tests were complete; as a result, the design had to be scrapped and the process restarted. On simpler designs, this kind of iterative test and verification approach might have been workable, but with the increasing complexity of emissions requirements and the need to reduce fuel consumption, the Sealing Products Group had no choice but to turn things around much faster while vastly reducing the amount of time and effort dedicated to testing.

SIMULATION IN THE EARLY DESIGN STAGE

Reorienting an engineering organization to support analysis-led design does not happen overnight. It is a gradual process that has been under way at the Sealing Products Group for years. Although early simulation applications and computer hardware put limitations on analysis-led design, the original goal was always to achieve 100% simulation before prototyping. The group is not quite there, but advances in technology are allowing it to get close. The group is working toward a system simulation approach coupled with individual component simulation, and today multidisciplinary CAE groups are leveraging simulation tools from a variety of companies to analyze and test designs for everything related to structural and thermal stress, durability, tribology, and computational fluid dynamics (CFD). In addition, the use of CFD and finite element analysis (FEA) has expanded over the years and now is applied to a wide range of applications in the base engine area as well as in other powertrain components.

The first leg of the journey was to identify the main outputs that could be simulated without taking into account any specific process flow. At this early stage it is necessary to determine whether it is preferable to simulate and test for durability or instead to evaluate the stress and strain of a product to avoid overdesigning from a materials standpoint. It helps to have a highly-trained CAE analyst involved in this step as well as test engineers who can develop the material properties required for the simulation.

Mapping out process flow is the next logical step. As manager of advanced engineering, I took on that key role, and the process required a couple of months. Instead of hunkering down with consultants behind closed doors, the start-up team involved engineers early on to get their input on defining the processes and identifying areas in which simulation might fit. Taking a bottom-up approach instead of mandating process changes from top management goes a long way toward ensuring buy-in and getting the broader engineering community to adopt the new practices.

Once the group became accustomed to the changes, no one questioned the CAE tools or the analysis-led design approach. In fact, it was at that point that engineers began looking for additional areas in which to apply simulation. Rather than let simulation expand organically, the team realized that it needed to organize and manage its growth. Simulation islands had begun to spring up, with different product teams using different software and different approaches that did not allow them to collaborate and reuse the results easily. An incredible amount of data was being created from the ongoing simulation efforts, and there needed to be a cohesive way to store the information and make it widely accessible.

At the same time, other engineering groups within Dana were facing similar challenges. At that point the global CAE teams within the engineering group decided to create a CAE Council, a formal body that would establish a standardized set of software and simultaneously create best practices so that the company as a whole would approach analysis-led design in a consistent manner. Established around seven years ago, the council meets at least once a quarter either virtually or face to face. The CAE Council defined a core portfolio of six CAE packages, including Abaqus from Dassault’s SIMULIA brand and Altair Hyperworks, and has nurtured partnerships with those vendors that give Dana input into how the tools will evolve. The CAE Council also is steering future directions around analysis-led design, including a pilot Simulation Lifecycle Management (SLM) project spearheaded by the Sealing Products Group that is intended to create a one-version-of-the-truth repository for all the simulation data.

Years into the journey, the biggest lesson learned is patience. Transitioning from many CAE tools to a standardized suite takes time; in fact, it took the Dana group nearly three years to make the switch, and during that time it had to incur the cost of some overlap in licensing fees. There was also a time lag before all the divisions were on the same renewal cycle for hardware upgrades, which was necessary for the company to maintain a consistent hardware platform to run the power-hungry simulation software.

Although the Dana Sealing Products Group is very close to its goal of 100% simulation for testing, that goal remains a moving target. The more simulation is implemented, the more possibilities come in sight. There may be no official end to this journey, and the Dana team has never lost touch with its well-defined strategy and the mission it envisioned for analysis-led design.