Thermo-economic Multi-objective Optimization Research Articles

Thermo-economic multi-objective optimization of the liquid air energy storage system

Liquid Air Energy Storage (LAES) is a promising energy storage technology for large-scale application in future energy systems with a higher renewable penetration. However, most studies focused on the thermodynamic analysis of LAES, few studies on thermo-economic optimization of LAES have been reported so far. Thus, this work focuses on the multi-objective optimization of LAES by using non-dominated sorting genetic algorithm (NSGA-II), taking the round trip efficiency (RTE) and economic indicators as the optimization objectives. Three major results were obtained from this work. First, the NSGA-II-based optimization framework is able to determine the optimal design and operational parameters of LAES under different configurations and scenarios, including the optimal charging and discharging pressure, heat transfer areas, and mass flow rates of hot and cold storage media etc. It is shown that the increase of energy efficiency by 9 % ~ 14 % and a decrease of exergy destruction by 16 % were seen. Secondly, the design and operational guidelines of LAES can be derived from the optimization. The optimal charging pressure was found to vary between 13 and 15 MPa, and the optimal discharging pressure is between 9 and 12 MPa, depending on the machines' efficiencies and pinch points of heat exchangers of a LAES system. Finally, the Pareto Fronts of capital expenditure, energy efficiency and the occupied space energy density of a LAES system provide system operators good operational and investment advice. Specifically, the RTE of the LAES increasing by 1 % is at the cost of increasing the capital cost by 0.5–1 %. In this study, if the investment budget is over 48 M£, a LAES system with three-stage compressors and four-stage turbines presents better trade-off between RTE and investment cost than the three-stage and four-stage systems. Overall, this work provides, for the first time, an NSGA-II-based optimization framework capable of determining the optimal design and operational parameters of LAES, informing the stakeholders of the design guidelines and investment guidance under different scenarios.

Optimizing Solar Energy Harvesting through Integrated Organic Rankine Cycle–Reverse Osmosis Systems: A Techno–Economic Analysis

When it comes to seawater desalination in the small- to medium-electricity ranges, the organic Rankine cycle (ORC) powered by solar energy stands out as the most energy-efficient technology currently available. Various solar techniques have been developed to capture and absorb solar energy. Among them, the parabolic trough collector (PTC) has gained recognition as a low-cost solar thermal collector with a long operating life. This study investigates the thermodynamic performance and economic parameters of a PTC-powered ORC using Dowtherm A and toluene as working fluids for the solar cycle and ORC cycle, respectively. Thermo-economic multi-objective optimization and decision-making techniques are applied to assess the system’s performance. Four key parameters are analyzed for their impact on exergy efficiency and total hourly cost. Using TOPSIS decision-making, the best solution from the Pareto frontier is identified, featuring an ORC exergy efficiency of 30.39% and a total hourly cost of 39.38 US$/h. The system parameters include a mass flow rate of fresh water at 137.7 m3/h, a total output net power of 577.9 kJ/kg, and a district heating supply of 1074 kJ/kg. The cost analysis reveals that the solar collector represents approximately 68% of the total hourly cost at 26.77 US$/h, followed by the turbine, thermoelectric generator, and reverse osmosis (RO) unit.

Thermoeconomic multiobjective optimization of tobacco drying heat pump recovering waste heat from monocrystal silicon furnace based on SVR ANN model in Southwest China

AbstractGreat quantities of energy are consumed by heat pump drying systems (HPDSs), such as tobacco drying. It can be reduced by increasing evaporating temperature using waste heat. In this paper, based on the case of two main industries in southwest China (monocrystalline silicon industry and tobacco industry), a novel integrated HPDS especially for the tobacco drying using waste heat from single crystal silicon furnaces is proposed. It is then analyzed from an energetic and economical perspective, investigating the effects of heat exchanger areas on system performance. To simultaneously minimize system CO2 emissions and total annual cost (TAC), a multiobjective optimization using nondominated sorting genetic algorithm is conducted based on the support vector regression model, which has been rarely reported for integrated HPDS improved by waste heat. The final optimum solution on the Pareto optimal front is selected using different decision‐making methods (LINMAP, TOPSIS, and fuzzy decision method), and are compared with the performance of the initial system. The results show that the TOPSIS method is most suitable in three decision‐making methods with a great reduction in (−12.7%) and nearly unchanged in TAC (+0.5%) compared with the initial solution. And the decreases in and TAC of the optimized system is as large as 50% and 1/3, compared with traditional vapor compression heat pump dryer without heat recovery of the monocrystal silicon furnace.

Multi-objective optimization of heat exchange network and thermodynamic cycles integrated system for cooling and power cogeneration

Thermodynamic cycles and heat exchange of process streams are effective waste heat recovery technologies, and their cooperation will make the use of energy more diversely and efficiently. To this end, a novel integrated system including compression-absorption cascade refrigeration system (CACRS), organic Rankine cycle (ORC) and heat exchanger network (HEN) is presented for cooling and power cogeneration and simultaneously performing the heat exchange of process streams. To achieve the optimal design of the integrated system, a thermo-economic multi-objective optimization model is developed for balancing the economic and thermodynamic objectives, along with optimizing the operating conditions and configuration structure simultaneously. Two cases in different application scenarios are studied. Compared with the literature, the economic cost and exergy destroy are reduced by 1.6% and 31.5%, respectively, demonstrating the superiority of the proposed method in improving energy efficiency and reducing energy losses. Furthermore, the conflicting relationship between economic and thermodynamic objectives is verified and the trade-off solution with both favorable economic and thermodynamic performances is determined for both cases. Compared with the optimal solutions with solo objective of economy and exergy, the exergy destroy and economic cost of the trade-off solution for case 1 are decreased by 315 kW and 50,063$/y, and for case 2 the decrease are 750 kW and 112,678 $/y, respectively.

Multi-objective thermo-economic optimization of Collins cycle

Many large scientific projects are emerging worldwide with the development of high energy physics nowadays. The indispensable subsystem, helium cryo-plants for such projects require extremely high energy consumption and total annual cost (TAC). In order to reduce energy consumption and TAC, multi-objective thermo-economic optimization that adopted non-dominated sorting genetic algorithm-II (NSGA-II) for helium cryo-plants is proposed in this work. As a typical helium liquefaction cycle, Collins cycle is selected as the optimization object. Both the exergetic efficiency (ηEx) and the TAC are set as objective parameters. The decision parameters, which include discharge pressure of compressor, flow fraction of expanders and effectiveness of heat exchangers, are optimized simultaneously. Linear programming technology of multidimensional analysis preference (LINMAP) is utilized as an example to select the optimal solution from the multi-objective optimization results. Compared to the maximum ηEx result, the LINMAP result reduces the TAC by 23.95% at the cost of 9.03% reduction in ηEx. In the proposed approach, eight decision parameters can be optimized simultaneously and the designed cryo-plant considers both economic and thermodynamic criteria, which is feasible for practical engineering project. Besides, alternative solution under limited investment situation is provided.

Thermo-economic multi-objective optimization of an innovative Rankine–organic Rankine dual-loop system integrated with a gas engine for higher energy/exergy efficiency and lower payback period

Thermo-economic multi-objective optimization of an innovative Rankine–organic Rankine dual-loop system integrated with a gas engine for higher energy/exergy efficiency and lower payback period

Different nanofluids as coolant in heat exchanger network: Thermoeconomic modeling and multi-objective optimization

Modeling and optimization of a multi tube heat exchanger (MTHE) network considering the effects of different nanoparticles on the tube side are carried out using Fast and elitist non-dominated sorting genetic algorithm. After thermal modeling in [Formula: see text] method, optimization is performed by increasing the effectiveness and decreasing total annual cost as two objective functions using eight design parameters such as number of MTHE and particles volumetric concentration. In addition, optimization is performed at three various cold mass flow rates and different nanoparticles including Al2O3, CuO and ZrO2 and results are compared with the base fluid (water). For the reliability of the present code, the modeling results are validated with the results obtained from both the numerical and experimental model. The results show that the optimal Pareto front is improved in nanoparticles case, and the rate of improvement in CuO nanoparticles case, especially in higher effectiveness and lower cold mass flow rate is more significant compared with the other studied cases. In addition, because of improvement in the thermal performance of MTHE network with nanoparticles, the heat transfer surface area and consequently the total volume of MTHE network for the fixed values of effectiveness are noticeably reduced. Finally, the effects of design parameters versus effectiveness are demonstrated and discussed.

Thermo-economic optimization of a Rankine cycle used for waste-heat recovery in biogas cogeneration plants

In a typical biogas cogeneration plant, a part of the exhaust gas energy is used for heating buildings within the plant. However, a certain amount of this energy remains unused. This study examined the utilization of this waste-heat through the Rankine cycle and organic Rankine cycle. A multiobjective thermo-economic optimization procedure of a waste-heat recovery unit installed at the exit of an engine before the engine cooling fluid–exhaust gas heat exchanger is proposed herein. The optimization procedure includes sizing all heat exchangers in the waste-heat recovery unit based on the measured Colburn and friction factors. The thermo-economic optimization was performed to investigate the maximal power output and the minimal payback period while preserving the function of the heating system. The procedure was applied to a biogas power plant with two engines (mass flow rate of the exhaust gases from each engine was 1.77 kg/s at a temperature of 410 °C). The electrical efficiency of this system was 42.1% and the measured overall yearly energetic efficiency was 66.7%. Optimization shows that the waste-heat recovery unit based on Rankine cycle is more economical than the unit based on the organic Rankine cycle using toluene. The electrical efficiency of the entire power plant increased by 2.97% and the payback period of the investment was 6.8 years, while the Levelized Cost of Electricity was 0.0419 $/kWh. The proposed method could be used to analyze the investment profitability of waste-heat utilization in other cogeneration plants.

A Thermo-Economic Multi-Objective Optimization Model for Cooling and Power Cogeneration with Multiple Waste Heat Recovery Technologies

A Thermo-Economic Multi-Objective Optimization Model for Cooling and Power Cogeneration with Multiple Waste Heat Recovery Technologies

WITHDRAWN: Multi-objective thermoeconomic optimization of innovative CCHP system driven by solar energy integrated with thermal energy storage

Abstract An efficient innovative combined cooling, heating and power (CCHP) system driven by solar energy with thermal energy storage is proposed and investigated. The system is a modified configuration of Rankine and ejector refrigeration cycles, integrated in such a way that it can operate on complete CHP or CCP modes by regulating the extracted mass flow ratio from the power turbine. Another interesting feature is employment of environmentally-friendly working fluids, namely CO2 and N2O. To enhance the system performance booster compressor is employed in refrigeration loop to increase the cooling production and thermoelectric generators are used to recover some part of the cycle waste heat. Feasibility analysis, parametric investigation and multi-objective thermoeconomic optimization are conducted to examine the system performance at all the range of practical operating/design conditions. The results indicated better performance of N2O compared to CO2 as the working fluid in terms of power generation, exergy efficiency and L C O E for all the operating conditions. Under the optimal operation obtained by multi-criteria optimization, thermal efficiency and L C O C H E values, respectively are 40.32% and 15.32 $/GJ for N2O working fluid. In addition, a comparison with similar previously proposed CCHP systems has indicated superiority of present CCHP system at the similar operating conditions.

Thermo-economic multi-objective optimization of an innovative cascaded organic Rankine cycle heat recovery and power generation system integrated with gas engine and ice thermal energy storage

Abstract For providing cooling, heating and electricity loads of buildings with high thermal efficiency and low energy consumption, an innovative cascaded organic Rankine cycle (CORC), an electrical chiller (with Vapor compression refrigeration cycle, VCR) and an ice thermal energy storage system (ITES) are integrated with a gas engine (GE). CORC heat recovery and power generation system with two high and low temperature loops uses the gas engine exhaust as heat source and generate electricity in an innovative heat recovery cogeneration plant. VCR-ITES provides the cooling demand. It shifts the electricity consumption from on-peak hours to off-peak low load hours (23–8). The electricity consumption of VCR-ITES is estimated based on variable cooling load during a year and not based on the cooling load at the hottest day in the year. Thermo-economic modeling and multi-objective optimizing the new proposed integrated system (GE-CORC-VCR+ITES) are performed to find the required capacity of equipment. After optimizing procedure, three 393 kW gas engines are selected. Results for CORC show that HT loop with R11 working fluid generated 75.6 kW and LT loop with R152a working fluid generated 72.9 kW (148.5 kW in sum) power output. Moreover, the thermal efficiency of CORC as well as overall thermal and exergy efficiency of integrated system were 23%, 68% and 63% respectively. The innovative CORC with dual loop configuration had higher net power output, higher thermal efficiency and lower investment cost per unit of power output ($/W) in comparison with a single loop ORC and other dual loop ORCs. VCR-ITES also had 44.2% lower energy consumption, 43.9% lower emission and 64% lower electricity cost in comparison with that for simple VCR system. Results for the proposed integrated system are also compared with that for the traditional system (buying electricity from the grid, generating heat by a hot water boiler and providing cooling load by an electrical chiller), the reduction in annual cost of buying electricity from the grid was 1.35 × 105 $/year (61.5%), also the annual income from selling electricity was estimated to be 9.8 × 105 $/year, the annual fuel cost consumption reduced due to heat recovery for 9.8 × 104 $/year (31%), and the annual CO2 and NOx emission production decreased for 3.02 × 104 $/year. The payback period of the optimized integrated system is 3.63 years.

Multi-Objective Thermo-Economic Optimization of a Combined Organic Rankine Cycle (ORC) System Based on Waste Heat of Dual Fuel Marine Engine and LNG Cold Energy Recovery

In this paper, a combined organic Rankine cycle (ORC) system that can effectively utilize the cold energy of Liquefied Nature Gas (LNG) and the waste heat of dual fuel (DF) marine engine was proposed. Particularly, the engine exhaust gas and the jacket cooling water of the DF marine engine were used as heat sources. Firstly, a thorough assessment of thermo-economic performance was conducted for the combined ORC system using 11 environmentally friendly working fluids (WFs). Afterwards, the effects of evaporation and condensation pressures on the net output work, energy efficiency, exergy efficiency, total investment cost and payback period were examined. Furthermore, the thermo-economic performances of the ORC system were optimized via multi-objective optimization with a genetic algorithm. Finally, exergy destructions and investment costs of each component under the optimal operating conditions were analyzed to make suggestions for further improvement. The results show that R1150-R1234yf-R600a and R170-R1270-R152a are the two most promising WF combinations. The exergy destruction of the combined ORC system mainly exists in heat exchangers. Through WF optimization, the exergy destruction in the intermediate heat exchanger was reduced by 18.99%. The proportion of expanders investment cost could be greater than 50% and the payback period of the combined ORC system varies in the range of 7.68–9.43 years. This study demonstrated that the selection of WF and the optimization of operating conditions had important potential to improve thermo-economic performances of ORC systems.

Multi-objective thermo-economic optimization of biomass retrofit for an existing solar organic Rankine cycle power plant based on NSGA-II

Non-dominated sorting genetic algorithm (NSGA-II) was deployed in this paper for multi-objective thermo-economic optimization of biomass retrofit for an existing solar organic Rankine cycle (ORC) power plant. The existing plant consists of a field of linear Fresnel collectors (LFC), integrated directly with two-tank thermal energy storage (TES) system, which interfaces with ORC power block. The real solar-ORC plant currently runs at Ottana, Italy, albeit with some technical challenges basically due to inconsistent availability of solar irradiation. In order to upgrade the plant, a novel scheme had been proposed to install a biomass unit in parallel to the solar field, such that both LFC/TES and biomass furnace could directly and independently satisfy fractional thermal input requirement of the ORC. Being a retrofit system, existing design parameters of all the already operating units were imposed as equality constraints in this study, and the combustion excess air, as well as pinch point temperature difference of furnace heat exchangers that optimize the hybrid plant were investigated. Results showed that biomass mass flow rate of 0.133 kg/s and investment cost rate of 57 €/h are optimal for the studied biomass retrofit scheme. At this optimum point, excess air was obtained as 56%, furnace heater pinch point temperature difference as 28.8 °C and air pre-heater pinch point temperature difference as 38.5 °C. More generally, results showed that excess air value of less than 100%, furnace heater pinch point temperature difference of less than 80 °C, and air pre-heater pinch point temperature difference of less than 80 °C would optimize the studied biomass retrofit scheme.

A thermo-economic multi-objective optimization model for simultaneous synthesis of heat exchanger networks including compressors

Two significant forms of energy widely used in chemical industries are heat and work related to temperature and pressure manipulation. Since complex relationship exists in these strongly interacting properties (heat, work, temperature, pressure), it is essential to investigate work and heat integration as a whole. In this paper, an enhanced stage-wise superstructure is proposed that involves simultaneous optimization of compressor placement and heat integration for each pressure-changing sub-stream in stages. It explicitly considers non-isothermal mixing in each stage and enables the optimized selection of pre-coolers, end-heaters as well as end-coolers to adjust temperature requirements. A novel thermo-economic multi-objective mixed-integer nonlinear programming (MINLP) model is formulated to synthesize sub and above-ambient heat exchanger networks between constant-pressure streams and pressure-changing streams with multi-stream compression. The new model aims to achieve the optimal balance between thermodynamic and economic performances, with the objective of minimizing exergy consumption and total annual cost (TAC), respectively. Three case studies are conducted, where the results illustrate the well-known trade-off between thermodynamic and economic objective that is a decrease of 12.6%, 7.6%, 23.8% in TAC, while exergy consumption is increased by 14.8%, 12.8%, 4%. The Pareto curve is plotted for decision-makers to determine the optimal alternatives in terms of process requirement.

Multi-objective thermo-economic optimization of a combined organic Rankine cycle and vapour compression refrigeration cycle

This study focuses on the multi-objective optimization of a combined power (organic Rankine cycle) and vapour compression refrigeration cycle based on heat source temperatures ranging from 120 °C to 150 °C. The primary purpose is to achieve an optimal system through the use of efficiency and cost functions. The size of the heat exchangers and turbines (indicated by the total heat transfer coefficient UAtotal and size parameter SPtotal, respectively) used in the system affect the cost function of the system, whereas the efficiency function of the system is affected by the thermal efficiency (ηth) and the irreversibility ratio (IR value, representing the total exergy destruction) of the system. The sensitivity analysis conducted herein revealed that the ηth value increased by 107.9% when the evaporator pressure was varied from the minimum to the maximum value within the bound constraints, whereas the UAtotal value increased by 15.5%. The system was optimized based on six input parameters. The optimization results indicated that the system optimized for R236ea provided the lowest cost and the lowest system efficiency, system optimized for R245ca provided the highest cost and the highest system efficiency, and the system optimized for R245fa was between the two above-mentioned extremes in terms of cost and efficiency. At a heat source temperature of 150 °C and with R245fa as the ORC fluid, the optimum UAtotal, ηth, IR, and SPtotal values were 99.6 kW/K, 35.8%, 54.2%, and 0.386 dm, respectively.

Optimum performance of a single effect desalination unit integrated with a SOFC system by multi-objective thermo-economic optimization based on genetic algorithm

A solid oxide fuel cell (SOFC) integrated with single effect desalination (SED) unit is modeled and optimized from exergoeconomic, enviroeconomic and exergoenvironmental points of view. A multi-criterion optimization technique based on genetic algorithm in the form of three various scenarios is accomplished. In scenario I (exergoeconomic optimization), the total exergy efficiency (ηe,t) and total cost rate (Z˙t) of the hybrid system are assumed as two objective function, while in scenario II (enviroeconomic optimization), the CO2 emission rate (EMI) and total cost rate (Z˙t) of the hybrid system are considered as the two objectives. Eventually, in scenario III (exergoenvironmental optimization), the total exergy efficiency (ηe,t) and the CO2 emission rate (EMI) are presumed as the optimization functions. In various scenarios, optimization technique is carried out with the aim of maximizing the ηe,t and minimizing the EMI andZ˙t. The multi-objective optimization results show that among different scenarios, the minimum total cost rate and CO2 emission rate occurs in the Scenario II, while the maximum total exergy efficiency occur in the Scenario I. In addition, it is revealed that, at the optimal conditions, the maximum net electrical power is achieved by Scenario I.

Multi-objective thermo-economic optimization of organic Rankine cycle (ORC) power systems in waste-heat recovery applications using computer-aided molecular design techniques

In this paper, we develop a framework for designing optimal organic Rankine cycle (ORC) power systems that simultaneously considers both thermodynamic and economic objectives. This methodology relies on computer-aided molecular design (CAMD) techniques that allow the identification of an optimal working fluid during the thermo-economic optimization of the system. The SAFT-γ Mie equation of state is used to determine the necessary thermodynamic properties of the designed working fluids, with critical and transport properties estimated using empirical group-contribution methods. The framework is then applied to the design of sub-critical and non-recuperated ORC systems in different applications spanning a range of heat-source temperatures. When minimizing the specific investment cost (SIC) of these systems, it is found that the optimal molecular size of the working fluid is linked to the heat-source temperature, as expected, but also that the introduction of a minimum pinch point constraint that is commonly employed to account for inherent trade-offs between system performance and cost is not necessary. The optimal SICs of waste-heat ORC systems with heat-source temperatures of 150 °C, 250 °C and 350 °C are £10120, £4040 and £2910 per kW, when employing propane, 2-butane and 2-heptene as the working fluids, respectively. During a set of MINLP optimizations of the ORC systems with heat-source temperatures of 150 °C and 250 °C, it is found that 1,3-butadiene and 4-methyl-2-pentene are the best-performing working fluids, respectively, with SICs of £9640 per kW and £4000 per kW. These substances represent novel working fluids for ORC systems that cannot be determined a priori by specifying any working-fluid family or by following traditional methods of testing multiple fluids. Interestingly, the same molecules are identified in a multi-objective optimization considering both the total investment cost and net power output. These findings highlight the power of this approach as it enables the selection of novel working fluids while optimizing ORC systems using single or multiple thermo-economic performance indicators.

Thermoeconomic multi-objective optimization of an organic Rankine cycle (ORC) adapted to an existing solid waste power plant

In this paper, thermodynamic and thermoeconomic analyses, and also optimization of an organic Rankine cycle (ORC) were performed. The system was adapted to an existing solid waste power plant with a 5.66 MW installed power capacity in order to produce additional power from the exhaust gas. The actual operating data of the plant were utilized during all stages of the analyses. The originality of this paper is based on the analysis of the possibility of the energy conversion of an exhaust gas with a temperature of 566 °C into the electricity by utilizing an ORC system in the concept of waste-to-energy. Four different working fluids: toluene, octamethyltrisiloxane (MDM), octamethyl cyclotetrasiloxane (D4) and n-decane were considered and analyzed for the current system. This is also another novelty of this study due to lack of such a study, in the open literature, that deals with an ORC utilized for a typical municipal solid waste power plant. According to the thermoeconomic analyses, toluene was found to be the optimum working fluid with the maximum power output of 584.6 kW and the exergy efficiency of 15.69%. The optimization of the cycle was performed by using the non-dominated sorting genetic algorithm method (NSGA-II) in MATLAB software environment. The optimization results were compared and the deviations of the net power output and the total cost rate were evaluated as −5.89%, −3.51 $/h for toluene; 0.96%, −3.60 $/h for MDM; 8.45%, −2.04 $/h for D4 and 2.00%, −5.54 $/h for n-decane, respectively.

Investigation and assessment of a novel solar-driven integrated energy system

In this paper, a novel integrated energy system driven by solar power is proposed. A concentrated solar trough system is utilized in integration with organic Rankine cycle, absorption cooling system, desalination unit and electrolyzer, for the purpose of polygeneration. The proposed system produces hydrogen, cooling, fresh water, and domestic hot water along with electric power production. The system is analyzed thermodynamically, and its overall performance is assessed through energy and exergy efficiencies. The effects of varying several operating parameters and conditions on the performance are investigated through parametric studies. The cost rate is estimated at different operating points. The overall thermoeconomic multi-objective optimization study shows two extremes of 39% and 21.7% as maximum and minimum overall exergy efficiencies, respectively, as achieved at cost rate of 309.56 $/h and 241.7 $/h, for each corresponding case, respectively.

Thermo-Economic Multiobjective Optimization of a LOW Temperature Organic Rankine Cycle for Energy Recovery

In last decades the scarcity of combustible oil around the world has promoted the quest of new processes to produce power from alternative energy sources. The conventional Rankine cycle with water as working fluid, it is a good choice to convert heat into electricity but inefficient in temperatures below 350 C. Using an organic compound as working fluid the Rankine cycle (Called Organic Rankine Cycle) improves the cycle efficiency and can reduce the economy of the process for energy recovery from low temperature sources. In this work we proposed a set of organic compounds and a scenario of process to obtain simultaneously both optimum values of compositions of the mixture (used as working fluid) and operating conditions of the cycle for a given low temperature source. As design goals we set the minimization of total annual cost and the maximization of thermal efficiency. Because these two goals are in conflict the design problem was posed as a non-linear multi-objective optimization problem with thermodyn...