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This paper defines the Multidisciplinary Design Optimization (MDO) as a new field of research endeavor and as an aid in the design of engineering systems. It examines the MDO conceptual components in relation to each other and defines their functions.
This study presents a neutronics-based assessment of the feasibility and viability of transmuting six major long-lived fission products (LLFPs) from light-water reactors, namely 99 Tc, 129 I, 79 Se, 93 Zr, 126 Sn, and 135 Cs, within the blanket region of a tokamak fusion reactor, using the MIT ARC design as a concrete fusion configuration. Monte Carlo neutronics simulations were performed to evaluate LLFP transmutation and to compare the results with a reference boiling water reactor (BWR). The results indicate that transmutation of all six LLFPs is neutronics-feasible in fusion reactors, with transmutation half-lives significantly shorter than their natural decay half-lives. For elemental targets, transmutation of 135 Cs, 126 Sn, and 93 Zr was found potentially viable, as the net mass transmuted exceeded that achievable in the reference BWR under identical target volume and irradiation time. When isotopically separated targets were considered, transmutation of 126 Sn and 93 Zr appeared potentially viable. A parametric study demonstrated that plasma geometry modifications can enhance local neutron flux, increasing the transmuted 93 Zr mass by approximately 33% and reducing the transmutation half-life from approximately 240 years to 180 years. Repositioning the target and adjusting material layer thickness reduced the transmutation half-life of 93 Zr to 67 years and increased the net mass transmuted by a factor of 50. Furthermore, these results demonstrate that fusion reactors can enable LLFP transmutation beyond the practical limits of thermal fission reactors and highlight the critical role of reactor and blanket design optimization. Engineering and fuel-cycle considerations required for deployment are beyond the scope of this neutronics-focused study.
Unit cell design remains a major challenge for interlocking metasurfaces, a promising joining technology for dissimilar materials, due to the complex, competing, multivariate design space and the need for rapid adaptation to varying performance requirements. This study explores Conditional Diffusion Models as a design optimization tool for interlocking metasurfaces. Given the complex, competing, multivariate design space for interlocking metasurfaces, unit cell design remains a major challenge for this joining technology. We trained a conditional diffusion model on 25,000 finite element analysis-simulated interlocking metasurface unit cells to generate designs with tailored thermo-mechanical properties (tensile strength, shear strength, and thermal conductivity) based on specified performance criteria. The model demonstrated a success rate of approximately 72 % in producing designs that met specified property bounds. The conditional diffusion model generated both thermally resistive and conductive designs, revealing clear trends in design characteristics: taller, dendritic structures were advantageous for tensile loads, while shorter, robust designs excelled in shear applications. Our findings indicate that the model's performance is more influenced by the breadth of the design space than by the quantity of training data, highlighting the importance of expansive design domains for generating innovative solutions. This work establishes conditional diffusion models as a highly efficient and adaptable tool for rapid interlocking metasurface unit cell design, paving the way for advancements in multi-material joining technologies, as well as highlighting the justification to leverage conditional diffusion models as design tools across complex design domains.
Parallelization of Rocket Engine System Software (PRESS) project is part of a collaborative effort with Southern University at Baton Rouge (SUBR), University of West Florida (UWF), and Jackson State University (JSU). The project has started on October 19, 1995, and after a three-year period corresponding to project phases and fiscal-year funding by NASA Lewis Research Center (now Glenn Research Center), has ended on October 18, 1998. The one-year no-cost extension period was granted on June 7, 1998, until October 19, 1999. The aim of this one year no-cost extension period was to carry out further research to complete the work and lay the groundwork for subsequent research in the area of aerospace engine design optimization software tools. The previous progress for the research has been reported in great detail in respective interim and final research progress reports, seven of them, in all. While the purpose of this report is to be a final summary and an valuative view of the entire work since the first year funding, the following is a quick recap of the most important sections of the interim report dated April 30, 1999.
Increased electrification of aircraft systems, a growing trend in the aircraft industry, affects subsystems that have historically been pneumatically driven by the engine. Optimized design of propulsion and power systems must account for the requirements of these subsystems. One such subsystem, the wing ice protection system, is the focus of this paper. A preliminary computational icing analysis has been conducted using the LEWICE and ANSYS FENSAP-ICE software to characterize the requirements of a thermal ice protection system for three More Electric Aircraft concepts. This paper summarizes the methodology, simulation execution, and icing conditions used for the analysis as well as discusses the results, observed trends, and impacts to system design. This initial analysis indicates that the computed heat requirements for the wing ice protection systems are not within the capabilities of known traditional systems. A discussion of potential methods for reducing the heat flow requirement by the ice protection system is included. Potential refinements to the analysis to improve the accuracy are also discussed.
A definition of the multidisciplinary design optimization (MDO) is introduced, and functionality and relationship of the MDO conceptual components are examined. The latter include design-oriented analysis, approximation concepts, mathematical system modeling, design space search, an optimization procedure, and a humane interface.
Papers from the Third International Conference on Inverse Design Concepts and Optimization in Engineering Sciences (ICIDES) are presented. The papers discuss current research in the general field of inverse, semi-inverse, and direct design and optimization in engineering sciences. The rapid growth of this relatively new field is due to the availability of faster and larger computing machines.
A fusion engineering demonstration facility would be the first step in the commercial fusion plant developmental pathway that aims to be an engineering demonstration of tritium self-sufficiency. One of the primary requirements for tritium self-sufficiency, as well as to ensure low plant tritium release to the external environment, is to minimize the tritium loss through the internal components, which requires accurate predictions of the tritium behavior for a wide range of materials and system conditions. This grant addressed the lack of a comprehensive model which accounts for particular conditions, such as the significance of temperature fields and neutronics information, and the systematic uncertainty quantification of associated material properties that impact tritium generation, utilization, and loss mechanisms in the blanket.
A fusion engineering demonstration facility would be the first step in the commercial fusion plant developmental pathway that aims to be an engineering demonstration of tritium self- sufficiency. One of the primary requirements for tritium self-sufficiency, as well as to ensure low plant tritium release to the external environment, is to minimize the tritium loss through the internal components, which requires accurate predictions of the tritium behavior for a wide range of materials and system conditions. This grant addressed the lack of a comprehensive model which accounts for particular conditions, such as the significance of temperature fields and neutronics information, and the systematic uncertainty quantification of associated material properties that impact tritium generation, utilization, and loss mechanisms in the blanket.
The design optimization of air-breathing propulsion engine concepts has been accomplished by soft-coupling the NASA Engine Performance Program (NEPP) analyzer with the NASA Lewis multidisciplinary optimization tool COMETBOARDS. Engine problems, with their associated design variables and constraints, were cast as nonlinear optimization problems with thrust as the merit function. Because of the large number of mission points in the flight envelope, the diversity of constraint types, and the overall distortion of the design space; the most reliable optimization algorithm available in COMETBOARDS, when used by itself, could not produce satisfactory, feasible, optimum solutions. However, COMETBOARDS' unique features-which include a cascade strategy, variable and constraint formulations, and scaling devised especially for difficult multidisciplinary applications-successfully optimized the performance of subsonic and supersonic engine concepts. Even when started from different design points, the combined COMETBOARDS and NEPP results converged to the same global optimum solution. This reliable and robust design tool eliminates manual intervention in the design of air-breathing propulsion engines and eases the cycle analysis procedures. It is also much easier to use than other codes, which is an added benefit. This paper describes COMETBOARDS and its cascade strategy and illustrates the capabilities of the combined design tool through the optimization of a high-bypass- turbofan wave-rotor-topped subsonic engine and a mixed-flow-turbofan supersonic engine.
The problem is to find a global minimum for the Problem P. Necessary and sufficient conditions are available for local optimality. However, global solution can be assured only under the assumption of convexity of the problem. If the constraint set S is compact and the cost function is continuous on it, existence of a global minimum is guaranteed. However, in view of the fact that no global optimality conditions are available, a global solution can be found only by an exhaustive search to satisfy Inequality. The exhaustive search can be organized in such a way that the entire design space need not be searched for the solution. This way the computational burden is reduced somewhat. It is concluded that zooming algorithm for global optimizations appears to be a good alternative to stochastic methods. More testing is needed; a general, robust, and efficient local minimizer is required. IDESIGN was used in all numerical calculations which is based on a sequential quadratic programming algorithm, and since feasible set keeps on shrinking, a good algorithm to find an initial feasible point is required. Such algorithms need to be developed and evaluated.
Some current research work conducted at the University of Michigan is described to illustrate efforts for incorporating knowledge in optimization in a nontraditional way. The incorporation of available knowledge in a logic structure is examined in two circumstances. The first examines the possibility of introducing global design information in a local active set strategy implemented during the iterations of projection-type algorithms for nonlinearly constrained problems. The technique used algorithms for nonlinearly constrained problems. The technique used combines global and local monotinicity analysis of the objective and constraint functions. The second examines a knowledge-based program which aids the user to create condigurations that are most desirable from the manufacturing assembly viewpoint. The data bank used is the classification scheme suggested by Boothroyd. The important aspect of this program is that it is an aid for synthesis intended for use in the design concept phase in a way similar to the so-called idea-triggers in creativity-enhancement techniques like brain-storming. The idea generation, however, is not random but it is driven by the goal of achieving the best acceptable configuration.
Computational support of the engineering design process routinely requires mathematical models of behavior to inform designers of the system response to external stimuli. However, designers also need to know the effect of the changes in design variable values on the system behavior. For large engineering systems, the conventional way of evaluating these effects by repetitive simulation of behavior for perturbed variables is impractical because of excessive cost and inadequate accuracy. An alternative is described based on recently developed system sensitivity analysis that is combined with extrapolation to form a model of design. This design model is complementary to the model of behavior and capable of direct simulation of the effects of design variable changes.
A gas turbine engine blade design is optimized using STAEBL. To validate the STAEBL analysis, the optimized blade design is analyzed using MARC, MHOST and BEST3D. The results show good agreement between STAEBL, MARC, and MHOST. The conclusion is that STAEBL can be used to optimize an engine blade design.
An integrated system for the multidisciplinary analysis and optimization of airframe and propulsion design parameters is being developed. This system is known as IPAS, the Integrated Propulsion/Airframe Analysis System. The traditional method of analysis is one in which the propulsion system analysis is loosely coupled to the overall mission performance analysis. This results in a time consuming iterative process. First, the engine is designed and analyzed. Then, the results from this analysis are used in a mission analysis to determine the overall aircraft performance. The results from the mission analysis are used as a guide as the engine redesigned and the entire process repeated. In IPAS, the propulsion system, airframe, and mission are closely coupled. The propulsion system analysis code is directly integrated into the mission analysis code. This allows the propulsion design parameters to be optimized along with the airframe and mission design parameters, significantly reducing the time required to obtain an optimized solution.
An integrated system for the multidisciplinary analysis and optimization of airframe and propulsion design parameters is being developed. This system is known as IPAS, the Integrated Propulsion/Airframe Analysis System. The traditional method of analysis is one in which the propulsion system analysis is loosely coupled to the overall mission performance analysis. This results in a time consuming iterative process. First, the engine is designed and analyzed. Then, the results from this analysis are used in a mission analysis to determine the overall aircraft performance. The results from the mission analysis are used as a guide as the engine is redesigned and the entire process repeated. In IPAS, the propulsion system, airframe, and mission are closely coupled. The propulsion system analysis code is directly integrated into the mission analysis code. This allows the propulsion design parameters to be optimized along with the airframe and mission design parameters, significantly reducing the time required to obtain an optimized solution.
The design optimization of a reactor-Stirling heat-pipe-cooled radiator is presented. The radiator is a self-deploying concept that uses individual finned heat pipe 'petals' to reject waste heat from a Stirling engine. Radiator optimization methodology is presented, and the results of a parametric analysis of the radiator design variables for a 100-kW(e) system are given. The additional steps of optiminzing the radiator resulted in a net system mass savings of 3 percent.
Progress in the development of a performance optimized engine system design for an advanced LOX/hydrogen expander cycle engine is reported. Analysis of the components and engine and the resulting drawings is discussed. The status of the orbit transfer vehicle liquid engine transient simulation computer model is given.