Exergy Analysis and Design Optimization for Aerospace Vehicles and Systems

A review on exergy analysis of aerospace power systems

Coal to SNG: Technical progress, modeling and system optimization through exergy analysis

The optimal design of multidisciplinary systems under uncertainty involves three types of iterative analyses- multidisciplinary analyses, reliability analyses, and optimization. If these processes are carried out in a nested manner in reliability based multidisciplinary design optimization (RBMDO), the computational expense can be enormous. Computationally efficient simultaneous analysis and design (SAND) or All-AtOnce methods have been developed earlier for deterministic MDO. Single loop RBDO methods have also been developed to integrate reliability analysis and optimization in a single loop. This paper develops a novel formulation of RBMDO problems with both system and component level reliability constraints. The formulation allows for solution with a single design optimization loop by using the KKT optimality conditions of the first-order reliability method (FORM) as constraints in the design optimization along with disciplinary consistency constraints. Alternative solution processes which remove the FORM MPP’s from the decision space and many constraints from the problem are developed. The alternative solution methods are more efficient and more robust than using nonlinear programming to solve the single loop formulation. A numerical example is solved with the two proposed solution algorithms. I. Introduction In the design of multidisciplinary systems it is often necessary to make decisions under uncertainty. This requires that multidisciplinary systems modeling be integrated with uncertainty analysis and optimization. A common example of such an engineering design application would be the design of an aircraft wing under uncertain aerodynamic loading conditions, with multiple structural components with uncertain capacities, such that the entire structural system achieves a prescribed level of reliability. The problem has coupled physics, in that the pressure distribution is dependent upon the deflection, and the deflection is dependent on the pressure distribution. Such designs have been performed using multidisciplinary optimization (MDO). Other examples where MDO may be applied include electronics packaging, in which the disciplines of heat transfer and circuit analysis are coupled, the design of new types of aircraft and integrating them into an existing fleet of aircraft, and even the management of interconnected homeland infrastructures. While MDO has matured with the development of different types of algorithms for various types of problems and design organizations, there has been little work to incorporate reliability analysis into MDO. However, system and component reliabilities are often a major concern in the design of multidisciplinary systems. MDO can be computationally expensive due to the need to achieve consistency across multiple disciplinary analysis codes; each disciplinary analysis code may be computationally expensive to run. Further, the optimal design of multidisciplinary systems under uncertainty involves three types of iterative procedures- multidisciplinary analyses, reliability analyses, and optimization. The integration of these three procedures is referred to in this paper as reliability based multidisciplinary design optimization (RBMDO). If these processes are carried out simultaneously, the computational expense can be enormous. Computational savings can often be achieved with simultaneous analysis and design (SAND) or All-At-Once methods, which allow for the solution of the multidisciplinary analyses and the optimization in one single loop. Single loop RBDO methods allow for the integration of reliability analysis and optimization in a single loop. Applying SAND and single-loop RBDO together may allow for large computational savings when applied to problems in RBMDO. This paper develops a novel formulation of RBMDO problems with both system and component level reliability constraints based on the SAND method for MDO and by use of the KKT conditions of the first order reliability method (FORM). The resulting formulation may be solved as a standard nonlinear programming problem. While the single loop formulation presented in this paper is a solution of the RBMDO problem, robustness and efficiency are improved through two improved algorithms which can remove the MPP’s from the decision space, thereby significantly reducing the optimizer’s workload.

The design of complex aerospace systems is a multidisciplinary design optimization (MDO) problem involving the interaction of multiple disciplines. However, because of the necessity of evaluating expensive black-box simulations, the enormous computational cost of solving MDO problems in aerospace systems has also become a problem in practice. To resolve this, metamodel-based design optimization techniques have been applied to MDO. With these methods, system models can be rapidly predicted using approximate metamodels to improve the optimization efficiency. This paper presents an overall survey of metamodel-based MDO for aerospace systems. From the perspective of aerospace system design, this paper introduces the fundamental methodology and technology of metamodel-based MDO, including aerospace system MDO problem formulation, metamodeling techniques, state-of-the-art metamodel-based multidisciplinary optimization strategies, and expensive black-box constraint-handling mechanisms. Moreover, various aerospace system examples are presented to illustrate the application of metamodel-based MDOs to practical engineering. The conclusions derived from this work are summarized in the final section of the paper. The survey results are expected to serve as guide and reference for designers involved in metamodel-based MDO in the field of aerospace engineering.

Exergy analysis is a thermodynamic analysis technique based primarily on the Second Law of Thermodynamics. As an alternative to energy analysis, exergy analysis provides an illuminating means of assessing and comparing processes and systems rationally and meaningfully. Consequently, exergy analysis can assist in improving and optimizing designs. Two key features of exergy analysis are (1) it yields efficiencies which provide a true measure of how nearly actual performance approaches the ideal, and (2) it identifies more clearly than energy analysis the types, causes and locations of thermodynamic losses.

In this work, we have considered a non-canonical scalar field dark energy model in the framework of flat FRW background. It has also been assumed that the dark matter sector interacts with the non-canonical dark energy sector through some interaction term. Using the solutions for this interacting non-canonical scalar field dark energy model, we have investigated the validity of generalized second law (GSL) of thermodynamics in various scenarios using first law and area law of thermodynamics. For this purpose, we have assumed two types of horizons viz apparent horizon and event horizon for the universe and using first law of thermodynamics, we have examined the validity of GSL on both apparent and event horizons. Next, we have considered two types of entropy-corrections on apparent and event horizons. Using the modified area law, we have examined the validity of GSL of thermodynamics on apparent and event horizons under some restrictions of model parameters.

Thermoelectric (TE) generation is becoming a valuable and promising research direction. Many researchers have carried out system analysis and performance optimization of thermoelectric technologies based on the generalized thermoelectric energy balance equations. However, it is assumed that TE legs have no heat exchange with the ambient except at the junctions of the hot and cold ends where heat flows in and out. Based on basic thermoelectric effects and fundamental theories of heat transfer, a detailed derivation of the revised generalized thermoelectric energy equations considering convective heat transfer between TE legs and the ambient has been carried out. Irreversible heat transfer processes have been analyzed by employing energy analysis based on the first law of thermodynamics and exergy analysis based on the second law of thermodynamics. The results show that convective heat transfer leads to a decrease in both energy and exergy efficiencies: the rate and magnitude of the decrease in exergy efficiency are greater than those of the decrease in energy efficiency. The exergy efficiency is relatively high despite the low energy efficiency in operation, revealing the features and advantages of thermoelectric generators (TEGs) in low‐grade energy utilization. For TEG efficient operation, the load resistance value should match the system's internal resistance, or at least be greater than that, to avoid a sharp drop in power output and efficiencies. In an attempt at theoretical analysis, the concept of entransy was first introduced into thermoelectric analysis, yielding two concise relational equations which reflect the intrinsic link between Carnot cycle efficiency, energy efficiency, exergy efficiency, and entransy flow transfer efficiency. The entransy analysis based on the index of entransy flow transfer efficiency, together with energy analysis and exergy analysis, may be a novel and valuable guideline for the operation and optimization of TEGs, which needs to be further investigated.

Chapter 10 - Exergy Analysis Applied to Geothermal Power Systems

Enhancing energy and exergy performance of a cascaded refrigeration cycle: Optimization and comparative analysis

Chapter 10 - Exergy Analysis Applied toGeothermal Power Systems

Bioenergy, sustainability, and the second law

Applications of the second-law in numerical analysis are reviewed. Numerical stability is analyzed by practical application of the second law of thermodynamics as a measure of stability. The second law is implemented as a statistical law, known as Gauss’ principle, relating the concavity property of the entropy to the logarithm of a probability density. Nonlinear stability is implied by arguing that average variations in the solution have an upper bound, as indicated by a pair of generalized entropy metrics. The concavity property of entropy prescribes the proper formula for the entropy balance equation by identifying the non-negative entropy generation term and placing all other terms on the opposite side of the equality. Conversely, a systematic strategy for constructing a balance of exergy equation suitable for thermodynamic processes is reviewed. The concept of entropy and exergy represent complementary formulations of the second-law principle. The generality of the concepts and principles involved demonstrate a wide-range of practical applications, from a simplifled derivation of the well-known formula for the second-law in thermodynamics to modern applications of the second law in numerical analysis and computational physics. Of particular interest to the author is the application of the second-law principle in the analysis and design of complex physical systems by using a common metric and universal principle for high-fldelity design analysis and optimization.

In the work reported in this paper, we have analyzed generalized Chaplygin gas (GCG) and modified generalized Chaplygin gas (MGCG) in an interacting scenario. The equation of state parameter has been analyzed in both the cases and the stability of the models has been discerned through squared speed of sound. Stability against gravitational perturbations has been observed for both GCG and MGCG interacting with pressureless dark matter. Also, the generalized second law (GSL) of thermodynamics has been tested for different enveloping horizons and validity of GSL has been observed throughout. Furthermore, f(T) gravity has been reconstructed with GCG and MGCG and phantom behaviour has been observed through reconstructed EoS parameters. The squared speed of sound has been derived for f(T) gravity and stability of the model has been established through its positivity.

Fluctuation theorems and the second law of thermodynamics are powerful relations constraining the behavior of out-of-equilibrium systems. While there exist generalizations of these relations to feedback controlled quantum systems, their applicability is limited, in particular when considering strong and continuous measurements. In this Letter, we overcome this shortcoming by deriving a novel fluctuation theorem, and the associated second law of information thermodynamics, which remain applicable in arbitrary feedback control scenarios. In our second law, the entropy production is bounded by the coarse-grained entropy production that is inferrable from the measurement outcomes, an experimentally accessible quantity that does not diverge even under strong continuous measurements. We illustrate our results by a qubit undergoing discrete and continuous measurement, where our approach provides a useful bound on the entropy production for all measurement strengths.

We provide a short review of the recent developments in entropic cosmology based on two thermodynamic laws of the apparent horizon, namely the first and the second laws of thermodynamics. The first law essentially provides the change in entropy of the apparent horizon during the cosmic evolution of the universe; in particular, it is expressed by TdS=−d(ρV)+WdV (where W is the work density and other quantities have their usual meanings). In this way, the first law actually links various theories of gravity with the entropy of the apparent horizon. This leads to a natural question—“What is the form of the horizon entropy corresponding to a general modified theory of gravity?”. The second law of horizon thermodynamics states that the change in total entropy (the sum of horizon entropy + matter fields’ entropy) with respect to cosmic time must be positive, where the matter fields behave like an open system characterised by a non-zero chemical potential. The second law of horizon thermodynamics importantly provides model-independent constraints on entropic parameters. Finally, we discuss the standpoint of entropic cosmology on inflation (or bounce), reheating and primordial gravitational waves from the perspective of a generalised entropy function.