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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 1,567 records · Page 87

Characteristics of a gelled liquid hyprogen polyphenylene oxide (PPO) foam open-cell insulation system, phase 1

A large scale gel production and storage facility and a small scale facility, the latter used for detailed visual examination of the gel/PPO foam interface, were developed. A subcontract was given to investigate techniques for the production of gelled liquid hydrogen, develop a process design for scale-up to a 1.89 cu m (500 gallon) gel production and storage facility, determine gel transfer characteristics, determine the solubility rate of gaseous helium in the gel, and investigate the gross gel/PPO foam interfacial phenomena. An inside-tank process for scaled-up production of gelled liquid hydrogen was selected. No detectable gel structure degradation occurred during repeated shearing. The viscosity of gelled liquid hydrogen at shear rates of 300/sec and higher is 2 to 5-fold greater than that of neat liquid hydrogen. No clogging problems were encountered during the transfer of gelled liquid hydrogen through warmed transfer lines. The solubility rate of helium in liquid hydrogen was significantly reduced by the presence of gel structure. The boil-off rates from gelled liquid hydrogen were reduced from 25 to 50 percent compared to those observed for the neat liquid hydrogen under compatible conditions. The polyphenylene oxide (PPO) foam insulation was found to be compatible with liquid ethane.

Source record↗

Simultaneous in-flight calibrations of the Galileo science platform and attitude control subsystems

This paper presents a design metholodology and simulation study results for a combined star scanner-gyro-scan platform in-flight calibration for the dual spin Galileo spacecraft. The design process involves three separate parts: the construction of an error model, development of the calibration model, and the selection of the appropriate estimation technique. The major innovative contribution lies in the development of the first two parts which are unique to the Galileo design. A unified procedure has been developed to allow simultaneous calibration of the three subsystems. However, provisions are also made in the software to calibrate each subsystem separately when the necessary a priori information is available.

Lai, J. Y.↗

Structural modeling for multicell composite rotor blades

Composite material systems are currently good candidates for aerospace structures, primarily for the design flexibility they offer, i.e., it is possible to tailor the material and manufacturing approach to the application. A working definition of elastic or structural tailoring is the use of structural concept, fiber orientation, ply stacking sequence, and a blend of materials to achieve specific performance goals. In the design process, choices of materials and dimensions are made which produce specific response characteristics, and which permit the selected goals to be achieved. Common choices for tailoring goals are preventing instabilities or vibration resonances or enhancing damage tolerance. An essential, enabling factor in the design of tailored composite structures is structural modeling that accurately, but simply, characterizes response. The objective of this paper is to present a new multicell beam model for composite rotor blades and to validate predictions based on the new model by comparison with a finite element simulation in three benchmark static load cases.

Rehfield, Lawrence W.↗

Development of ITM Oxygen Technology for Integration in IGCC and Other Advanced Power Generation DECISION POINT 1 UNDER PHASE 3

Air Products and the DOE have partnered over a number of years in the development of ITM Oxygen technology in support of gasification technology. Throughout this process, studies of application of the technology to IGCC and oxy-coal combustion have shown significant reduction in capital and operating costs compared to similar systems using conventional cryogenic air separation. Phase 3, the current phase of the program, focuses on the design, construction and operation of a 30- to 100-TPD pilot facility, the Intermediate Scale Test Unit (ISTU). Execution of this phase to date has resulted in significant advances in a number of areas including ceramic membrane material development, module design and production, ceramic-to-metal seal design, process control strategies, and engineering development of process cycles. Phase 3 will be complete upon successful operation of the ISTU in a series of tests making oxygen from ceramic membrane modules and producing power from a hot gas expander. Phase 3 work has extended beyond the planned schedule due to a delay in delivery of equipment from vendors. Air Products is currently managing the equipment delay by close involvement with the vendor to redesign the problematic equipment and oversee its fabrication. The result of these unforeseen challenges is that the ISTU project completion date has been delayed. Tight cost controls have been implemented both by DOE program management and APCI to meet budget constraints despite increased costs due to budget delays. Total project costs have increased in several areas. Increased costs in the ISTU project include purchased equipment, instruments, construction, and contractor engineering. Increased costs for other tasks include additional work in support of module production by Ceramatec, Inc, and increased Air Products labor for component testing. Air Products plans to complete testing as outlined in the SOPO and successfully complete all project objectives by the end of FY14.

Anderson, Lori↗

Advanced Strategy Guideline: Air Distribution Basics and Duct Design

This report discusses considerations for designing an air distribution system for an energy efficient house that requires less air volume to condition the space. Considering the HVAC system early in the design process will allow adequate space for equipment and ductwork and can result in cost savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗

Electronic Conductivity of Nanoporous Indium Oxide Derived from Sequential Infiltration Synthesis

Sequential infiltration synthesis (SIS) is a vapor phase synthetic method that enables the selective nucleation and growth of metal oxides within polymer volumes. The expanding palette of SIS materials and process designs enables tunability of the resulting material properties. We derive porous indium oxide thin films from the SIS of indium oxide using trimethyl indium and H 2 O 2 in polymethyl methacrylate films and observe the strong effect of SIS and post-deposition processing, which affords 7 orders of magnitude of tunability in electrical resistivity. While as-deposited hybrid nanocomposites show no measurable conductivity, high-temperature treatment in O 2 removes the polymer matrix and creates a porous nanocrystalline In 2 O 3 film with resistivities ranging from 10 3 to 10 5 Ω*cm, with lower resistivity correlated to larger grain sizes. Subsequent annealing in H 2 decreases the resistivity of films to less than 10 –2 Ω*cm. A clear correlation between increasing In 2 O 3 volume fraction, grain size, and carrier mobility is observed, which arises from increased percolation pathways, path length, and contact area in nanocrystalline In 2 O 3 films. Furthermore, this wide tunability demonstrates the importance of understanding growth mechanisms and processing conditions for functional materials development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Creation of Simulated Test Cases for the Oscillation Source Location Contest

This paper describes in detail the design process and creation of 13 oscillatory test cases for the IEEE and NASPI co-hosted Oscillation Source Locating Contest conducted in 2021. The challenges behind the 13 cases are fully demystified. Based on the philosophy, implementation considerations and techniques used for the case design presented in this paper, interested readers can create additional interesting cases for testing the efficiency of their oscillation source location methods.

ENERGY PLANNING, POLICY, AND ECONOMY↗

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗

Status of integrated multidisciplinary rotorcraft optimization research at the Langley Research Center

This paper describes a joint NASA/Army research activity at the Langley Research Center to develop optimization procedures aimed at improving the rotor blade design process by integrating appropriate disciplines and accounting for important interactions among the disciplines. The activity is being guided by a Steering Committee made up of key NASA and Army researchers and managers. The paper describes the optimization formulation in terms of the objective function, design variables, and constraints. The analysis aspects are discussed, and the interdisciplinary interactions are defined in terms of the information that must be transferred among disciplinary analyses as well as the trade-offs between disciplines in determining the details of the design. At this writing, some significant progress has been made. Results given in the paper represent accomplishments in rotor aerodynamic performance optimization for minimum horsepower, rotor dynamic optimization for vibration reduction, approximate analysis of frequencies and mode shapes, rotor structural optimization for minimum weight, and integrated aerodynamic load/dynamics optimization for minimum vibration and weight.

Mantay, Wayne R.↗

Design and test of a small two stage counter-rotating turbine for rocket engine application

The aerodynamic design and rig test evaluation of a small counter-rotating turbine system is described. The technology represented by this turbine is being developed for application in an advanced upper stage rocket engine turbopump. This engine will employ an oxygen/hydrogen expander cycle and achieve high performance through efficient combustion, high combustion pressure, and high area ratio exhaust nozzle expansion. Engine performance goals require that the turbopump drive turbines achieve high efficiency at low gas flow rates. The low flow rates result in very small airfoil diameter, height and chord. The high efficiency and small size requirements present a challenging turbine design problem. The unconventional approach employed to meet this challenge is described, along with the detailed design process and resulting airfoil configurations. The method and results of full scale aerodynamic performance evaluation testing of both one and two stage configurations, as well as operation without the secondary stage stator are presented. The overall results of this effort illustrate that advanced aerodynamic design tools and hardware fabrication techniques have provided improved capability to produce small high performance turbines for advanced rocket engines.

Huber, F. W.↗

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗

Application of the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

Systems analysis involves steady-state simulations of combined components to evaluate the steady-state performance, weight, and cost of a system; dynamic considerations are not included until later in the design process. The Dynamic Systems Analysis task, under NASAs Fixed Wing project, is developing the capability for assessing dynamic issues at earlier stages during systems analysis. To provide this capability the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) has been developed to design a single flight condition controller (defined as altitude and Mach number) and, ultimately, provide an estimate of the closed-loop performance of the engine model. This tool has been integrated with the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS 40k) engine model to demonstrate the additional information TTECTrA makes available for dynamic systems analysis. This dynamic data can be used to evaluate the trade-off between performance and safety, which could not be done with steady-state systems analysis data. TTECTrA has been designed to integrate with any turbine engine model that is compatible with the MATLAB Simulink (The MathWorks, Inc.) environment.

control↗

Path Toward a Unifid Geometry for Radiation Transport

The Direct Accelerated Geometry for Radiation Analysis and Design (DAGRAD) element of the RadWorks Project under Advanced Exploration Systems (AES) within the Space Technology Mission Directorate (STMD) of NASA will enable new designs and concepts of operation for radiation risk assessment, mitigation and protection. This element is designed to produce a solution that will allow NASA to calculate the transport of space radiation through complex computer-aided design (CAD) models using the state-of-the-art analytic and Monte Carlo radiation transport codes. Due to the inherent hazard of astronaut and spacecraft exposure to ionizing radiation in low-Earth orbit (LEO) or in deep space, risk analyses must be performed for all crew vehicles and habitats. Incorporating these analyses into the design process can minimize the mass needed solely for radiation protection. Transport of the radiation fields as they pass through shielding and body materials can be simulated using Monte Carlo techniques or described by the Boltzmann equation, which is obtained by balancing changes in particle fluxes as they traverse a small volume of material with the gains and losses caused by atomic and nuclear collisions. Deterministic codes that solve the Boltzmann transport equation, such as HZETRN [high charge and energy transport code developed by NASA Langley Research Center (LaRC)], are generally computationally faster than Monte Carlo codes such as FLUKA, GEANT4, MCNP(X) or PHITS; however, they are currently limited to transport in one dimension, which poorly represents the secondary light ion and neutron radiation fields. NASA currently uses HZETRN space radiation transport software, both because it is computationally efficient and because proven methods have been developed for using this software to analyze complex geometries. Although Monte Carlo codes describe the relevant physics in a fully three-dimensional manner, their computational costs have thus far prevented their widespread use for analysis of complex CAD models, leading to the creation and maintenance of toolkit-specific simplistic geometry models. The work presented here builds on the Direct Accelerated Geometry Monte Carlo (DAGMC) toolkit developed for use with the Monte Carlo N-Particle (MCNP) transport code. The workflow for achieving radiation transport on CAD models using MCNP and FLUKA has been demonstrated and the results of analyses on realistic spacecraft/habitats will be presented. Future work is planned that will further automate this process and enable the use of multiple radiation transport codes on identical geometry models imported from CAD. This effort will enhance the modeling tools used by NASA to accurately evaluate the astronaut space radiation risk and accurately determine the protection provided by as-designed exploration mission vehicles and habitats

Lee, Kerry↗

Application of the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

Systems analysis involves steady-state simulations of combined components to evaluate the steady-state performance, weight, and cost of a system; dynamic considerations are not included until later in the design process. The Dynamic Systems Analysis task, under NASAs Fixed Wing project, is developing the capability for assessing dynamic issues at earlier stages during systems analysis. To provide this capability the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) has been developed to design a single flight condition controller (defined as altitude and Mach number) and, ultimately, provide an estimate of the closed-loop performance of the engine model. This tool has been integrated with the Commercial Modular Aero-Propulsion System Simulation 40,000(CMAPSS40k) engine model to demonstrate the additional information TTECTrA makes available for dynamic systems analysis. This dynamic data can be used to evaluate the trade-off between performance and safety, which could not be done with steady-state systems analysis data. TTECTrA has been designed to integrate with any turbine engine model that is compatible with the MATLABSimulink (The MathWorks, Inc.) environment.

systems analysis↗

Astrobee Free-Flyer Nozzle Mechanism

This paper describes the development and design of the Astrobee Free-Flyer propulsion nozzle assemblies. As will be illustrated in this paper, the Free-Flyer nozzles are thrust control devices used to propel the Astrobee Free-Flyer robot autonomously inside the International Space Station (ISS). The development process, design evolution, and prototyping methods, are described. Key design features are discussed in greater detail to highlight how a seemingly simple design can present surprisingly large challenges. Several lessons learned are given.

Earl Daley↗

Creation of Simulated Test Cases for the Oscillation Source Location Contest: Preprint

This paper describes in detail the design process and creation of 13 oscillatory test cases for the IEEE and NASPI co-hosted Oscillation Source Locating Contest conducted in 2021. The challenges behind the 13 cases are fully demystified. Based on the philosophy, implementation considerations and techniques used for the case design presented in this paper, interested readers can create additional interesting cases for testing the efficiency of their oscillation source location methods.

ENERGY PLANNING, POLICY, AND ECONOMY↗

AbBERT: Learning Antibody Humanness via Masked Language Modeling

Understanding the degree of humanness of antibody sequences is critical to the therapeutic antibody development process to reduce the risk of failure modes like immunogenicity or poor manufacturability. We introduce AbBERT, a transformer-based language model trained on up to 20 million unpaired heavy/light chain sequences from the Observed Antibody Space database. We first validate AbBERT using a novel “multi-mask” scoring procedure to demonstrate high accuracy in predicting complementary determining regions—including the challenging hypervariable H3 region. We then demonstrate several uses of AbBERT at various points along the antibody design process. AbBERT enhances in silico antibody optimization via deep reinforcement learning by utilizing its learned embeddings as additional observations during optimization. Within a larger computational antibody design platform, AbBERT has been successfully applied as an additional design objective, where it displays strong correlations with computational tools predicting antibody structural stability. Finally, mutant antibody sequences that have been scored as unfavorable by AbBERT have shown corresponding low yields when expressed in cells. These use cases demonstrate the power of language modeling within computational antibody design.

Bioinformatics↗