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Results for “Optimal sizing method”

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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Improved method for transonic airfoil design-by-optimization

An improved method for use of optimization techniques in transonic airfoil design is demonstrated. FLO6QNM incorporates a modified quasi-Newton optimization package, and is shown to be more reliable and efficient than the method developed previously at NASA-Ames, which used the COPES/CONMIN optimization program. The design codes are compared on a series of test cases with known solutions, and the effects of problem scaling, proximity of initial point to solution, and objective function precision are studied. In contrast to the older method, well-converged solutions are shown to be attainable in the context of engineering design using computational fluid dynamics tools, a new result. The improvements are due to better performance by the optimization routine and to the use of problem-adaptive finite difference step sizes for gradient evaluation.

Kennelly, R. A., Jr.↗
NASA NTRS1983

Improved method for transonic airfoil design-by-optimization

An improved method for use of optimization techniques in transonic airfoil design is demonstrated. FLO6QNM incorporates a modified quasi-Newton optimization package, and is shown to be more reliable and efficient than the method developed previously at NASA-Ames, which used the COPES/CONMIN optimization problem. The design codes are compared on a series of test cases with known solutions, and the effects of problem scaling, proximity of initial point to solution, and objective function precision are studied. In contrast to the older method, well-converged solutions are shown to be attainable in the context of engineering design using computational fluid dynamics tools, a new result. The improvements are due to better performance by the optimization routine and to the use of problem-adaptive finite difference step sizes for gradient evaluation.

Kennelly, R. A., Jr.↗
NASA NTRS2003

Fiber Reinforcement Architectures of PMCs on the Hygrothermal-Mechanical Performance for Aeropropulsion Applications

A rigid lightweight sandwich support structure, for the combustor chamber of a new generation liquid propellant rocket engine, was designed and fabricated using Polymer Matric Composite (PMC) facesheet on a Ti honeycomb or Carbon foam core. The facesheet consisted of high stiffness carbon fiber, M40JB, and high temperature Polyimides, such as PMR-11-50 and HFPE-II. Six different fiber architectures; 4HS woven fabric, uni-fabric, woven-uni hybrid, stitched woven fabric, stitched uni-fabric and tri-axial braided structures have been investigated for optimum stiffness-thickness-weight-performance design criteria for the hygrothermal-mechanical propulsion service exposure conditions including rapid heating up to 200 F/sec, maximum operating temperature of 600 F, internal pressure up to 100 psi. An extensive property and performance database including dry-wet mechanical properties at both 25 F and 600 F in various loading modes, thermal and physical properties including blistering onset condition was developed for fiber architecture down-selection and design guidelines. Various optimized process methods including vacuum bag compression molding, solvent assistant RTM (SaRTM), resin film infusion (RFI) were utilized for PMC panel fabrication depending on the architecture type. In the case of stitched woven fabric architecture, the optimal stitch pattern was chosen in terms of stitch density and yarn size, based on both in-plane mechanical properties and blistering performance. Potential reduction of the in-plane properties transverse to the line of stitching was also evaluated. Attempt to correlate the experimental results with theoretical micro-mechanics predictions will be presented.

Shin, Eugene↗
DOE OSTI2020

Optimal Estimation Retrievals and Their Uncertainties: What Every Atmospheric Scientist Should Know

Remote sensing instruments are heavily used to provide observations for both the operational and research communities. These sensors do not provide direct observations of the desired atmospheric variables, but instead, retrieval algorithms are necessary to convert the indirect observations into the variable of interest. It is critical to be aware of the underlying assumptions made by many retrieval algorithms, including that the retrieval problem is often ill posed and that there are various sources of uncertainty that need to be treated properly. In short, the retrieval challenge is to invert a set of noisy observations to obtain estimates of atmospheric quantities. The problem is often complicated by imperfect forward models, by imperfect prior knowledge, and by the existence of nonunique solutions. Optimal estimation (OE) is a widely used physical retrieval method that combines measurements, prior information, and the corresponding uncertainties based on Bayes’s theorem to find an optimal solution for the atmospheric state. Furthermore, OE also allows the relative contributions of the different sources of error to the uncertainty in the final retrieved atmospheric state to be understood. Here, we provide a novel Python library to illustrate the use of OE for inverse problems in the atmospheric sciences. We introduce two example problems: how to retrieve drop size distribution parameters from radar observations and how to retrieve the temperature profile from ground-based microwave sensors. Using these examples, we discuss common pitfalls, how the various error sources impact the retrieval, and how the quality of the retrieval results can be quantified.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Elucidating metal–organic framework structures using synchrotron serial crystallography

Metal organic frameworks (MOFs) are porous crystalline materials that display a wide variety of physical and chemical properties. Their single crystal structure determination is often challenging because in most cases micro- or nano-sized crystals spontaneously form upon MOF synthesis, which cannot be recrystallized. The production of larger single crystals for structure determination involves optimizing, and thus modifying, the conditions of synthesis, in which success cannot be guaranteed. Failure to produce crystals suitable for single-crystal X-ray diffraction leaves the 3D structure of the MOF compound unknown, and scientists must resort to more challenging structure solution methods based on X-ray powder or electron diffraction data. These laborious tasks can be avoided by using serial crystallography techniques which merge data collected on many micro-crystals. Here, we report the application of three synchrotron serial crystallography methods. We call these “mesh”, “grid” and “mesh&collect” scans. “Still” images (no rotation) are collected in the mesh scan approach, whereas small rotational wedges are collected in the grid scan method. The third protocol, mesh&collect, combines the acquisition of still images and rotational wedges. Using these means, we determine the ab initio structure of benchmark MOFs, MIL-100(Fe) and ZIF-8, that differ largely in unit cell size. These methods are expected to be widely applicable and facilitate structure determination of many MOF microcrystalline systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

On the Rapid Calculation of Binding Affinities for Antigen and Antibody Design and Affinity Maturation Simulations

The accurate and efficient calculation of protein-protein binding affinities is an essential component in antibody and antigen design and optimization, and in computer modeling of antibody affinity maturation. Such calculations remain challenging despite advances in computer hardware and algorithms, primarily because proteins are flexible molecules, and thus, require explicit or implicit incorporation of multiple conformational states into the computational procedure. The astronomical size of the amino acid sequence space further compounds the challenge by requiring predictions to be computed within a short time so that many sequence variants can be tested. In this study, we compare three classes of methods for antibody/antigen (Ab/Ag) binding affinity calculations: (i) a method that relies on the physical separation of the Ab/Ag complex in equilibrium molecular dynamics (MD) simulations, (ii) a collection of 18 scoring functions that act on an ensemble of structures created using homology modeling software, and (iii) methods based on the molecular mechanics-generalized Born surface area (MM-GBSA) energy decomposition, in which the individual contributions of the energy terms are scaled to optimize agreement with the experiment. When applied to a set of 49 antibody mutations in two Ab/HIV gp120 complexes, all of the methods are found to have modest accuracy, with the highest Pearson correlations reaching about 0.6. In particular, the most computationally intensive method, i.e., MD simulation, did not outperform several scoring functions. The optimized energy decomposition methods provided marginally higher accuracy, but at the expense of requiring experimental data for parametrization. Within each method class, we examined the effect of the number of independent computational replicates, i.e., modeled structures or reinitialized MD simulations, on the prediction accuracy. We suggest using about ten modeled structures for scoring methods, and about five simulation replicates for MD simulations as a rule of thumb for obtaining reasonable convergence. We anticipate that our study will be a useful resource for practitioners working to incorporate binding affinity calculations within their protein design and optimization process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Perovskite Solar Module: Promise and Challenges in Efficiency, Meta‐Stability, and Operational Lifetime

Abstract Perovskite photovoltaics (PVs) are an emerging solar energy generation technology that is nearing commercialization. Despite the unprecedented progress in increasing power conversion efficiency (PCE) for perovskite solar cells (PSCs), up‐scaling lab‐made cells to solar modules remains a challenge. In this work, the recent progress of making perovskite mini‐modules is reviewed. In particular, a database summarizing the module size, performance, hysteresis, and operational lifetimes reported in the literature is built. After analyzing the performance losses from scaling PSCs to mini‐modules based on the data collected from the literature, the current key to high‐performance perovskite mini‐modules is found to be the coating method optimization. If the perovskite layer quality is well reserved, a >24% mini‐module efficiency is projected by only considering the losses from lateral resistivity and laser scribing area. Next, performance characteristics are explored including hysteresis and meta‐stable power outputs that must be overcome to correctly characterize perovskite modules. Finally, current challenges associated with the long‐term stability of perovskite modules are examined and the importance of such durability for commercialization is discussed. It is hoped that the findings in this review provide a bridge for the development of perovskite modules that will lead to commercialization in the near future.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Microreactor-liquid metal battery system in energy markets: An evaluation of potential costs, technology, and policy impacts

Microreactors represent an emerging innovation in the nuclear industry; yet have been overshadowed by their high capital costs. With the Inflation Reduction Act of 2022 (IRA), new opportunities have emerged to improve the economics of microreactor systems. This work examines liquid metal batteries (LMB) as a value-adding technology as part of microreactor-LMB systems within three U.S. electricity markets: ERCOT, PJM, and MISO. Our investigation considers key uncertainties: the cost of microreactors, the performance of LMBs, and the eligible tax credit levels. To this end, we use a dispatch optimization to trace not only the changes in system economics but also to provide a granular picture of energy delivery within the systems. We find that even with favorable costs for microreactors, significant regional variations in the project sizing and returns exist across the markets. Our heuristic method identifies their non-electric application potentials beyond electricity and technical requirements to maximize returns. The results suggest that 12–39 % of reactor heat could be cost-effectively diverted to produce more valuable by-products in U.S. markets. Including the impacts of tax credits, we establish the outcomes of each provision with varying rates. Coupling an LMB to a microreactor consistently improves the net present value of a microreactor compared to its standalone operation. In conclusion, for reasonable assumed conditions, we quantify a heterogeneous impact of round-trip efficiency (RTE) and extended LMB service life across the three markets—a one-year extension in LMB service life is roughly equivalent to a 2.11 % improvement in RTE for ERCOT, 1.16 % for PJM, and 1.04 % for MISO.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1987

Aeroassisted-vehicle design studies for a manned Mars mission

An aerobrake design that has matured over several years of development accounting for all of the important flow phenomenology which are characteristic of aerobraking vehicles is proposed as the mission baseline. Flight regimes and aerothermal environments for both Mars and Earth entry are calculated using advanced methods to account for real-gas, thermochemical, relaxation effects. The results are correlated with thermal-protection and structural requirements and mission performance capability. The importance of nonequilibrium radiative heating for Earth aerocapture is demonstrated. It is suggested that two aerobrakes of different sizes will produce optimal performance for the three phases of the mission (i.e., one aerobrake for Mars aerocapture and descent of the surface lander and another for Earth return).

Menees, Gene P.↗
NASA NTRS1987

Aeroassisted-vehicle design studies for a manned Mars mission

An aerobrake design accounting for all of the important flow phenomenology which are characteristic of aerobraking vehicles is proposed as the mission baseline. Flight regimes and aerothermal environments for both Mars and earth entry are calculated using advanced methods to account for real-gas, thermochemical, relaxation effects. The results are correlated with thermal-protection and structural requirements and mission performance capability. The importance of nonequilibrium radiative heating for earth aerocapture is demonstrated. It is suggested that two aerobrakes of different sizes will produce optimal performance for the three phases of the mission (i.e., one aerobrake for Mars aerocapture and descent of the surface lander and another for earth return).

Menees, Gene P.↗
NASA NTRS2001

Shape Optimization of Supersonic Turbines Using Response Surface and Neural Network Methods

Turbine performance directly affects engine specific impulse, thrust-to-weight ratio, and cost in a rocket propulsion system. A global optimization framework combining the radial basis neural network (RBNN) and the polynomial-based response surface method (RSM) is constructed for shape optimization of a supersonic turbine. Based on the optimized preliminary design, shape optimization is performed for the first vane and blade of a 2-stage supersonic turbine, involving O(10) design variables. The design of experiment approach is adopted to reduce the data size needed by the optimization task. It is demonstrated that a major merit of the global optimization approach is that it enables one to adaptively revise the design space to perform multiple optimization cycles. This benefit is realized when an optimal design approaches the boundary of a pre-defined design space. Furthermore, by inspecting the influence of each design variable, one can also gain insight into the existence of multiple design choices and select the optimum design based on other factors such as stress and materials considerations.

Papila, Nilay↗
NASA NTRS2004

Model of Atmospheric Links on Optical Communications from High Altitude

Optical communication links have the potential to solve many of the problems of current radio and microwave links to satellites and high-altitude aircraft. The higher frequency involved in optical systems allows for significantly greater signal bandwidth, and thus information transfer rate, in excess of 10 Gbps, and the highly directional nature of laser-based signals eliminates the need for frequency-division multiplexing seen in radio and microwave links today. The atmosphere, however, distorts an optical signal differently than a microwave signal. While the ionosphere is one of the most significant sources of noise and distortion in a microwave or radio signal, the lower atmosphere affects an optical signal more significantly. Refractive index fluctuations, primarily caused by changes in atmospheric temperature and density, distort the incoming signal in both deterministic and nondeterministic ways. Additionally, suspended particles, such as those in haze or rain, further corrupt the transmitted signal. To model many of the atmospheric effects on the propagating beam, we use simulations based on the beam-propagation method. This method, developed both for simulation of signals in waveguides and propagation in atmospheric turbulence, separates the propagation into a diffraction and refraction problem. The diffraction step is an exact solution, within the limits of numerical precision, to the problem of propagation in free space, and the refraction step models the refractive index variances over a segment of the propagation path. By applying refraction for a segment of the propagation path, then diffracting over that same segment, this method forms a good approximation to true propagation through the atmospheric medium. Iterating over small segments of the total propagation path gives a good approximation to the problem of propagation over the entire path. Parameters in this model, such as initial beam profile and atmospheric constants, are easily modified in a simulation such as this, which allows for the rapid analysis of different propagation scenarios. Therefore, this method allows the development of a near-optimal system design for a wide range of situations, typical of what would be seen in different atmospheric conditions over a receiving ground station. A simulation framework based upon this model was developed in FORTRAN, and for moderate grid sizes and propagation distances these simulations are computable in reasonable time on a standard workstation. This presentation will discuss results thus far.

Subich, Christopher↗
NASA NTRS2005

Fabrication of High Temperature Cermet Materials for Nuclear Thermal Propulsion

Processing techniques are being developed to fabricate refractory metal and ceramic cermet materials for Nuclear Thermal Propulsion (NTP). Significant advances have been made in the area of high-temperature cermet fuel processing since RoverNERVA. Cermet materials offer several advantages such as retention of fission products and fuels, thermal shock resistance, hydrogen compatibility, high conductivity, and high strength. Recent NASA h d e d research has demonstrated the net shape fabrication of W-Re-HfC and other refractory metal and ceramic components that are similar to UN/W-Re cermet fuels. This effort is focused on basic research and characterization to identify the most promising compositions and processing techniques. A particular emphasis is being placed on low cost processes to fabricate near net shape parts of practical size. Several processing methods including Vacuum Plasma Spray (VPS) and conventional PM processes are being evaluated to fabricate material property samples and components. Surrogate W-Re/ZrN cermet fuel materials are being used to develop processing techniques for both coated and uncoated ceramic particles. After process optimization, depleted uranium-based cermets will be fabricated and tested to evaluate mechanical, thermal, and hot H2 erosion properties. This paper provides details on the current results of the project.

Hickman, Robert↗
DOE OSTI2022

Optimization of Integrated Energy Systems

Integrated energy systems that couple nuclear power plants with additional products including hydrogen, storage, or synthetic fuels provide a more flexible energy source that can be more economical than generating electricity alone. Determining the size and shape of these systems and optimizing their operation is challenging. INL, through the IES program, has developed optimization software to help solve these challenges. Holistic Energy Resource Optimization Network (HERON) is a software tool to optimize the size and capacity of integrated energy systems using stochastic optimization. Optimization of Real-time Capacity Allocation (ORCA) is a software tool under development to perform real-time economic optimization of these systems using economic model predictive control. An overview of these tools and a discussion of their optimization methods will be presented in this talk.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

The Poisson–Boltzmann model for implicit solvation of electrolyte solutions: Quantum chemical implementation and assessment via Sechenov coefficients

Here, we present the theory and implementation of a Poisson-Boltzmann implicit solvation model for electrolyte solutions. This model can be combined with arbitrary electronic structure methods that provide an accurate charge density of the solute. A hierarchy of approximations for this model includes a linear approximation for weak electrostatic potentials, finite size of the mobile electrolyte ions, and a Stern-layer correction. Recasting the Poisson-Boltzmann equations into Euler-Lagrange equations then significantly simplifies the derivation of the free energy of solvation for these approximate models. The parameters of the model are either fit directly to experimental observables-e.g., the finite ion size-or optimized for agreement with experimental results. Experimental data for this optimization are available in the form of Sechenov coefficients that describe the linear dependence of the salting-out effect of solutes with respect to the electrolyte concentration. In the final part, we rationalize the qualitative disagreement of the finite ion size modification to the Poisson-Boltzmann model with experimental observations by taking into account the electrolyte concentration dependence of the Stern layer. A route toward a revised model that captures the experimental observations while including the finite ion size effects is then outlined. This implementation paves the way for the study of electrochemical and electrocatalytic processes of molecules and cluster models with accurate electronic structure methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Modeling and synthesis of multicomputer interconnection networks

The type of interconnection network employed has a profound effect on the performance of a multicomputer and multiprocessor design. Adequate models are needed to aid in the design and development of interconnection networks. A novel modeling approach using statistical and optimization techniques is described. This method represents an attempt to compare diverse interconnection network designs in a way that allows not only the best of existing designs to be identified but to suggest other, perhaps hybrid, networks that may offer better performance. Stepwise linear regression is used to develop a polynomial surface representation of performance in a (k+1) space with a total of k quantitative and qualitative independent variables describing graph-theoretic characteristics such as size, average degree, diameter, radius, girth, node-connectivity, edge-connectivity, minimum dominating set size, and maximum number of prime node and edge cutsets. Dependent variables used to measure performance are average message delay and the ratio of message completion rate to network connection cost. Response Surface Methodology (RSM) optimizes a response variable from a polynomial function of several independent variables. Steepest ascent path may also be used to approach optimum points.

Standley, Hilda M.↗
DOE OSTI2022

One‐Step Thermal Gradient‐ and Antisolvent‐Free Crystallization of All‐Inorganic Perovskites for Highly Efficient and Thermally Stable Solar Cells

Abstract All‐inorganic perovskites have emerged as promising photovoltaic materials due to their superior thermal stability compared to their heat‐sensitive hybrid organic–inorganic counterparts. In particular, CsPbI 2 Br shows the highest potential for developing thermally‐stable perovskite solar cells (PSCs) among all‐inorganic compositions. However, controlling the crystallinity and morphology of all‐inorganic compositions is a significant challenge. Here, a simple, thermal gradient‐ and antisolvent‐free method is reported to control the crystallization of CsPbI 2 Br films. Optical in situ characterization is used to investigate the dynamic film formation during spin‐coating and annealing to understand and optimize the evolving film properties. This leads to high‐quality perovskite films with micrometer‐scale grain sizes with a noteworthy performance of 17% (≈16% stabilized), fill factor (FF) of 80.5%, and open‐circuit voltage ( V OC ) of 1.27 V. Moreover, excellent phase and thermal stability are demonstrated even after extreme thermal stressing at 300 °C.

36 MATERIALS SCIENCE↗