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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,117 records · Page 62

Marrying Quality Assurance with Design Engineering - A Winning Partnership! But, a Cultural Divide?: Preprint

Investors would like to be confident that a PV plant will work as promised before investing large sums of money. Data showing that PV modules can withstand thousands of hours of accelerated testing are a comfort, but are not sufficient. An inability to be confident of every aspect of the system can motivate higher interest rates; high degradation or failure rates can substantially decrease the return on investment and the value of the plant for resale later on. In the end, a winning partnership is obtained when a carefully engineered, durable design is married with a robust quality management system and the marriage is extended across all parts of the value chain. However, this marriage is challenging because of the conventional cultural divide between design engineers and quality management specialists. This paper discusses the motivation for increased emphasis on quality assurance and describes three new standards that detail requirements for a higher level of quality assurance for 1) PV module manufacturing, 2) inverter and other balance-of-systems (BOS) manufacturing, and 3) control of the system installation and operation. The paper concludes with a discussion of the challenges and benefits of marrying the quality assurance program with further optimization of the PV system design.

14 SOLAR ENERGY↗

Further Development of an ISOCS - based Advanced In Situ Gamma Spectrometry Services Tool for Waste Measurements - 17452

Canberra's In Situ Object Counting System is an established tool used for gamma spectrometry allowing a physical representation of complex geometries and mathematical calculation of the calibration function while avoiding the need for radioisotope standards. The ISOCS Uncertainty Estimator tool can be used to calculate defensible systematic calibration uncertainties. However the uncertainties depend on knowledge of the properties of the item being measured and for poorly characterized materials these can be large, often leading to large costs for waste sentencing. An ISOCS-based advanced in-situ gamma spectrometry services tool has been developed to reduce those uncertainties. This system is based on generating and comparing a range of candidate geometry models that yield figures of merit indicative of improved consistency between modelled data and available diverse measurement data. The approach and results of initial performance testing have previously been published, demonstrating an analysis procedure and enhanced accuracy for measurement of a low density 200 litre waste drum, based on measurements with known sources placed at different positions. It was shown how the accuracy of assay of Am-241 in a light matrix can be significantly improved. Further analysis has now been performed, with reference to measurements of a second drum, containing a standard matrix of higher density, and with a multiple radionuclide line source (Ba-133, Cs-137, Eu-152 and Am-241). These measurements represent a more challenging waste assay scenario, corresponding to potentially much larger assay uncertainties. Our results show how the assay uncertainty can be reduced, by careful application of AIGS, from relative values of the order of 100% to a few 10's of %. Furthermore, we demonstrate, through extended analysis of the test drum data, how an AIGS measurement program can be optimized to reduce the number of required measurement positions substantially. This paper describes these new results with comment on their importance and potential application for real waste assay projects. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

CTF Parallel Performance Improvements

CTF is a modernized version of COBRA-TF (Coolant Boiling in Rod Arrays-Two Fluid), which is a thermal hydraulic (T/H) sub-channel code based on a two-phase, two-fluid model that formulates the conservation equations of mass, energy, and momentum for three fields of vapor, continuous liquid, and entrained liquid droplets. Under the Consortium for Advanced Simulation of Light Water Reactors (CASL) program sponsored by the U.S. Department of Energy, CTF is being further developed and improved for modeling and simulation of light water reactors. The code improvements for predicting T/H responses of pressurized water reactor (PWR) cores are focused on its applications to specific challenge problems deemed significant to the industry, such as departure from nucleate boiling (DNB) and crud-induced power shift. The code is also being used for T/H feedback in normal operating condition depletions in PWR and boiling water reactor designs in the reactor core simulator, Virtual Environment for Reactor Applications Core Simulator (VERA-CS), being developed by CASL. CTF modifications under the CASL program include software optimization, new closure models, and parallelization for modeling full reactor core T/H responses. The purpose of this work was to improve the parallel performance of CTF. CTF was originally parallelized via a domain-decomposition strategy using the Message Passing Interface (MPI), in which the basis of a solution domain was a physical assembly in the model. In other words, a user who wanted to perform a parallel solution with CTF had to provide the code one processor per assembly in the model (e.g., 56 cores for a 56 assembly quarter-core model, or 193 cores for a 193 assembly full-core model). This design was rigid, demanding a very specific number of processors for a model; furthermore, when CTF was run in VERA-CS-which typically uses thousands of processors- many processors sat idle during the CTF solve because CTF was unable to use any more processors than there are physical assemblies. This was not necessarily a problem if the CTF execution speed was very fast, but the average time spent in a CTF solve for prototypical PWR operating conditions was significant (i.e., over 20 % of the simulation wall time was being spent in CTF for a standard core depletion simulation). Larger, more computationally intensive simulations performed in support of the CASL DNB challenge problem demonstrated a need for improvements in this original parallelization approach. The specific goal of this work was to allow CTF to use more processors than there are physical assemblies in the model, which would not only speed up CTF and improve the overall efficiency of VERA-CS but also give users more-flexible options for executing their simulations. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Genetic Evolution of Shape-Altering Programs for Supersonic Aerodynamics

Two constrained shape optimization problems relevant to aerodynamics are solved by genetic programming, in which a population of computer programs evolves automatically under pressure of fitness-driven reproduction and genetic crossover. Known optimal solutions are recovered using a small, naive set of elementary operations. Effectiveness is improved through use of automatically defined functions, especially when one of them is capable of a variable number of iterations, even though the test problems lack obvious exploitable regularities. An attempt at evolving new elementary operations was only partially successful.

Kennelly, Robert A., Jr.↗

DUKSUP: A Computer Program for High Thrust Launch Vehicle Trajectory Design and Optimization

From the late 1960s through 1997, the leadership of NASAs Intermediate and Large class unmanned expendable launch vehicle projects resided at the NASA Lewis (now Glenn) Research Center (LeRC). One of LeRCs primary responsibilities --- trajectory design and performance analysis --- was accomplished by an internally-developed analytic three dimensional computer program called DUKSUP. Because of its Calculus of Variations-based optimization routine, this code was generally more capable of finding optimal solutions than its contemporaries. A derivation of optimal control using the Calculus of Variations is summarized including transversality, intermediate, and final conditions. The two point boundary value problem is explained. A brief summary of the codes operation is provided, including iteration via the Newton-Raphson scheme and integration of variational and motion equations via a 4th order Runge-Kutta scheme. Main subroutines are discussed. The history of the LeRC trajectory design efforts in the early 1960s is explained within the context of supporting the Centaur upper stage program. How the code was constructed based on the operation of the AtlasCentaur launch vehicle, the limits of the computers of that era, the limits of the computer programming languages, and the missions it supported are discussed. The vehicles DUKSUP supported (AtlasCentaur, TitanCentaur, and ShuttleCentaur) are briefly described. The types of missions, including Earth orbital and interplanetary, are described. The roles of flight constraints and their impact on launch operations are detailed (such as jettisoning hardware on heating, Range Safety, ground station tracking, and elliptical parking orbits). The computer main frames on which the code was hosted are described. The applications of the code are detailed, including independent check of contractor analysis, benchmarking, leading edge analysis, and vehicle performance improvement assessments. Several of DUKSUPs many major impacts on launches are discussed including Intelsat, Voyager, Pioneer Venus, HEAO, Galileo, and Cassini.

Launch vehicle performance optimization↗

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Program Review

This program developed an advanced model-based monitoring and model-predictive control algorithms for a coal fired power plant (CFPP), and deployed these algorithms in a real-time platform to demonstrate performance benefits for transient flexibility and plant operation efficiency. More specifically, the objectives were successfully achieved through a combination of (i) developing a high-fidelity transient plant model in Apros, which was used as a high-fidelity plant simulation between $100-50\% TMCR$ where TMCR denotes the turbine maximum continuous rating, i.e., baseload, (ii) developing a very fast physics-based reduced-order model (ROM) of the plant, which ran more than $100\times$ faster than real-time, enabling its use as real-time embedded model for model-based estimation (MBE) and model predictive control (MPC) (iii) implementing a real-time MBE based on ROM using a robust unscented Kalman filter (UKF) to continuously tune the ROM to match the measurements from high-fidelity Apros plant model despite significant plant-model mismatch, and thus, obtain a Digital Twin of the plant (iv) designing and implementing a real-time MPC with dual objectives of transient plant load tracking with high ramp rates and minimizing coal consumption, i.e., improving plant efficiency in the baseload-partload operation range of $100-50\% TMCR$. Each key element above was developed and tested individually, and has been reported in corresponding Topical Reports. Finally, all the individual elements were integrated in an overall closed-loop system, that was successfully tested in desktop Simulink test harness simulations with ROM or high-fidelity model as the plant. Thereafter, the Simulink implementation was used to auto-generate C-code and deploy as real-time Docker microservice containers in Linux, and validate that they can run in real-time in the hardware-in-the loop (HIL) setup and produce the same results as in Simulink. The results of the integrated simulation tests in Simulink as well as the real-time HIL deployment are documented in this final report, showing good load tracking for load ramps at $3-4\%/min$ ramp rates, and achieving up to $5.5\%$ reduction in coal relative to baseline operation at $50\% TMCR$ load. The desktop and HIL simulations show successful performance of the overall model based estimation and control solution and achieve the key objectives of the program for flexible, efficient and reliable operation of sub-critical coal fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

DUKSUP: A Computer Program for High Thrust Launch Vehicle Trajectory Design and Optimization

From the late 1960's through 1997, the leadership of NASA's Intermediate and Large class unmanned expendable launch vehicle projects resided at the NASA Lewis (now Glenn) Research Center (LeRC). One of LeRC's primary responsibilities --- trajectory design and performance analysis --- was accomplished by an internally-developed analytic three dimensional computer program called DUKSUP. Because of its Calculus of Variations-based optimization routine, this code was generally more capable of finding optimal solutions than its contemporaries. A derivation of optimal control using the Calculus of Variations is summarized including transversality, intermediate, and final conditions. The two point boundary value problem is explained. A brief summary of the code's operation is provided, including iteration via the Newton-Raphson scheme and integration of variational and motion equations via a 4th order Runge-Kutta scheme. Main subroutines are discussed. The history of the LeRC trajectory design efforts in the early 1960's is explained within the context of supporting the Centaur upper stage program. How the code was constructed based on the operation of the Atlas/Centaur launch vehicle, the limits of the computers of that era, the limits of the computer programming languages, and the missions it supported are discussed. The vehicles DUKSUP supported (Atlas/Centaur, Titan/Centaur, and Shuttle/Centaur) are briefly described. The types of missions, including Earth orbital and interplanetary, are described. The roles of flight constraints and their impact on launch operations are detailed (such as jettisoning hardware on heating, Range Safety, ground station tracking, and elliptical parking orbits). The computer main frames on which the code was hosted are described. The applications of the code are detailed, including independent check of contractor analysis, benchmarking, leading edge analysis, and vehicle performance improvement assessments. Several of DUKSUP's many major impacts on launches are discussed including Intelsat, Voyager, Pioneer Venus, HEAO, Galileo, and Cassini.

high thrust trajectory design↗

Speed Trajectory Optimization for a Heavy-Duty Truck Traversing Multiple Signalized Intersections: A Dynamic Programming Study

This paper explores the fuel savings that can be achieved by optimizing the speed trajectory of a heavy-duty truck traversing a sequence of intersections, under the assumptions that the behavior of the leading traffic and the timing of the traffic lights is known. Specifically, we look at the impact of corridor topology (i.e. green cycle lengths, phase offsets) on the expected fuel savings of the optimized trajectories. This is an important area of research because vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technology has the potential to allow autonomous vehicles to reduce fuel consumption, especially in urban and sub-urban driving scenarios. The literature tackles the problem of arterial corridor trajectory optimization, and shows the potential fuel saving benefits. However, previous research focuses primarily on passenger vehicles, and often limits its findings to specific case studies. The main contribution of this paper is to offer an estimate of the fuel saving potential - for heavy-duty trucks and under different corridor characteristics - of optimizing trajectories in an urban arterial with V2V and V21 capabilities.

42 ENGINEERING↗

Stacking-sequence optimization for buckling of laminated plates by integer programming

Integer-programming formulations for the design of symmetric and balanced laminated plates under biaxial compression are presented. Both maximization of buckling load for given total thickness, and the minimization of total thickness subject to a buckling constraint are formulated. The design variables that define the stacking sequence of the laminate are zero-one integers. It is shown that the formulation results in a linear optimization problem that can be solved on readily aviable software. Constraints on the stacking sequence such as a limit on the number of contiguous plies of the same orientation and limits on in-plane stiffnesses are easily accommodated. Examples are presented for graphite-epoxy plates under uniaxial and biaxial compression using a commercial software package based on the branch-and-bound algorithm.

Haftka, Raphael T.↗

Quantitative simulation of extraterrestrial engineering devices

This is a multicomponent, multidisciplinary project whose overall objective is to build an integrated database, simulation, visualization, and optimization system for the proposed oxygen manufacturing plant on Mars. Specifically, the system allows users to enter physical description, engineering, and connectivity data through a uniform, user-friendly interface and stores the data in formats compatible with other software also developed as part of this project. These latter components include: (1) programs to simulate the behavior of various parts of the plant in Martian conditions; (2) an animation program which, in different modes, provides visual feedback to designers and researchers about the location of and temperature distribution among components as well as heat, mass, and data flow through the plant as it operates in different scenarios; (3) a control program to investigate the stability and response of the system under different disturbance conditions; and (4) an optimization program to maximize or minimize various criteria as the system evolves into its final design. All components of the system are interconnected so that changes entered through one component are reflected in the others.

Arabyan, A.↗

Stacking-sequence optimization for buckling of laminated plates by integer programming

Integer-programming formulations for the design of symmetric and balanced laminated plates under biaxial compression are presented. Both maximization of buckling load for a given total thickness and the minimization of total thickness subject to a buckling constraint are formulated. The design variables that define the stacking sequence of the laminate are zero-one integers. It is shown that the formulation results in a linear optimization problem that can be solved on readily available software. This is in contrast to the continuous case, where the design variables are the thicknesses of layers with specified ply orientations, and the optimization problem is nonlinear. Constraints on the stacking sequence such as a limit on the number of contiguous plies of the same orientation and limits on in-plane stiffnesses are easily accommodated. Examples are presented for graphite-epoxy plates under uniaxial and biaxial compression using a commercial software package based on the branch-and-bound algorithm.

Haftka, Raphael T.↗

Data-Conforming Data-Driven Control: Avoiding Premature Generalizations Beyond Data

Data-driven and adaptive control approaches face the problem of introducing sudden distributional shifts beyond the distribution of data encountered during learning. Therefore, they are prone to invalidating the very assumptions used in their own construction. This is due to the linearity of the underlying system, inherently assumed and formulated in most data-driven control approaches, which may falsely generalize the behavior of the system beyond the behavior experienced in the data. This article seeks to mitigate these problems by enforcing consistency of the newly designed closed-loop systems with data and slowing down any distributional shifts in the joint state-input space. This is achieved through incorporating affine regularization terms and linear matrix inequality constraints to data-driven approaches, resulting in convex semi-definite programs that can be efficiently solved by standard software packages. We discuss the optimality conditions of these programs and then conclude this article with a numerical example that further highlights the problem of premature generalization beyond data and shows the effectiveness of our proposed approaches in enhancing the safety of data-driven control methods.

97 MATHEMATICS AND COMPUTING↗

Soft x ray window encapsulant for HgI2 detectors

HgI2 is an excellent semiconductor material for a low energy, room temperature x-ray spectrometer. The high values of the atomic numbers for its constituent elements gives high x-ray and gamma ray stopping power. The band gap of HgI2 is significantly higher than other commonly used semiconductors. Owing to the large value band gap, the leakage current for HgI2 devices is smaller, thus allowing low noise performance. Devices fabricated from HgI2 crystals have demonstrated energy resolution sufficient to distinguish the x-ray emission from the neighboring elements on the periodic table. Also the power requirements of HgI2 are very low. These characteristics make a HgI2 spectrometer an ideal component in a satellite based detection system. Unfortunately, HgI2 crystals tend to deteriorate with time, even if protected by standard semiconductor encapsulants. This degradation ruins the performance of the device in terms of its energy resolution and pulse amplitude. The degrading mechanism is believed to be material loss occurring from below the electrodes, due to high vapor pressure of HgI2 at room temperature. To address this major obstacle to rapid expansion of HgI2 technology, a research program aimed at improving device stability by encapsulation with inert polymeric materials was carried out. The program focused specifically on optimizing the encapsulant materials and their deposition techniques. The principal objectives for this program were device encapsulation, device testing, and accelerated testing to ensure very long term stability of these high resolution sensors. A variety of encapsulants were investigated with the selection criteria based on their chemical diffusion barrier properties, mechanical stability, reactivity, and morphology of encapsulant films. The investigation covered different classes of encapsulants including solvent based encapsulants, vapor deposited encapsulants, and plasma polymerized encapsulants. A variety of characterization techniques were employed to examine their effectiveness in stabilizing HgI2 devices; these included permeability evaluation, vacuum and heat testing, scanning electron microscopy (SEM) as well as studying the detector performance of coated detectors. The plasma polymerized films appear to have entirely solved the HgI2 degradation problem. Another achievement of this program was the development of an accelerated testing technique which correlates extremely well with long term tesing.

Entine, G.↗

Mass and Volume Optimization of Space Flight Medical Kits

Resource allocation is a critical aspect of space mission planning. All resources, including medical resources, are subject to a number of mission constraints such a maximum mass and volume. However, unlike many resources, there is often limited understanding in how to optimize medical resources for a mission. The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulates outcomes and describes the impact of medical events in terms of lost crew time, medical resource usage, and the potential for medically required evacuation. Previously published work describes an approach that uses the IMM to generate optimized medical kits that maximize benefit to the crew subject to mass and volume constraints. We improve upon the results obtained previously and extend our approach to minimize mass and volume while meeting some benefit threshold. METHODS We frame the medical kit optimization problem as a modified knapsack problem and implement an algorithm utilizing dynamic programming. Using this algorithm, optimized medical kits were generated for 3 mission scenarios with the goal of minimizing the medical kit mass and volume for a specified likelihood of evacuation or Crew Health Index (CHI) threshold. The algorithm was expanded to generate medical kits that maximize likelihood of evacuation or CHI subject to mass and volume constraints. RESULTS AND CONCLUSIONS In maximizing benefit to crew health subject to certain constraints, our algorithm generates medical kits that more closely resemble the unlimited-resource scenario than previous approaches which leverage medical risk information generated by the IMM. Our work here demonstrates that this algorithm provides an efficient and effective means to objectively allocate medical resources for spaceflight missions and provides an effective means of addressing tradeoffs in medical resource allocations and crew mission success parameters.

Monte Carlo Method↗