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At least 667 records · Page 37

The human role in space: Technology, economics and optimization

Man-machine interactions in space are explored in detail. The role and the degree of direct involvement of humans that will be required in future space missions are investigated. An attempt is made to establish valid criteria for allocating functional activities between humans and machines and to provide insight into the technological requirements, economics, and benefits of the human presence in space. Six basic categories of man-machine interactions are considered: manual, supported, augmented, teleoperated, supervised, and independent. Appendices are included which provide human capability data, project analyses, activity timeline profiles and data sheets for 37 generic activities, support equipment and human capabilities required in these activities, and cumulative costs as a function of activity for seven man-machine modes.

Hall, S. B.↗

Techno-economic projections for advanced small solar thermal electric power plants to years 1990-2000

Advanced technologies applicable to solar thermal electric power systems in the 1990-200 time-frame are delineated for power applications that fulfill a wide spectrum of small power needs with primary emphasis on power ratings less than 10MWe. Projections of power system characteristics (energy and capital costs as a function of capacity factor) are made based on development of identified promising technologies and are used as the basis for comparing technology development options and combinations of these options to determine developmental directions offering potential for significant improvements. Stirling engines, Brayton/Rankine combined cycles and storage/transport concepts encompassing liquid metals, and reversible-reaction chemical systems are considered for two-axis tracking systems such as the central receiver or power tower concept and distributed parabolic dish receivers which can provide efficient low-cost solar energy collection while achieving high temperatures for efficient energy conversion. Pursuit of advanced technology across a broad front can result in post-1985 solar thermal systems having the potential of approaching the goal of competitiveness with conventional power systems.

Fujita, T.↗

SEASAT economic assessment. Volume 10: The SATIL 2 program (a program for the evaluation of the costs of an operational SEASAT system as a function of operational requirements and reliability

The SATIL 2 computer program was developed to assist with the programmatic evaluation of alternative approaches to establishing and maintaining a specified mix of operational sensors on spacecraft in an operational SEASAT system. The program computes the probability distributions of events (i.e., number of launch attempts, number of spacecraft purchased, etc.), annual recurring cost, and present value of recurring cost. This is accomplished for the specific task of placing a desired mix of sensors in orbit in an optimal fashion in order to satisfy a specified sensor demand function. Flow charts are shown, and printouts of the programs are given.

Source record↗

Seasonal Cost-Benefit Analysis of Automated Distribution Feeder Upgrades with Advanced Mitigation Technologies

The increasing deployment of distributed solar photovoltaics (DPV) to meet clean energy goals can trigger adverse grid operation issues, such as voltage excursions and the violation of thermal loading constraints of the power delivery elements (e.g., lines and transformers) on the evolving electricity infrastructure. Such integration issues would require distribution upgrades with associated costs to mitigate them and to maintain reliable and resilient grid operating conditions. Traditional distribution network upgrade approaches use a specific single snapshot analysis that is overly conservative. This study considers a multi-time point analysis to capture both moderate (probable bounds) and extreme grid operating conditions using time points such as minimum load with minimum photovoltaics (PV), maximum load with maximum PV, maximum load with minimum PV, and minimum load with maximum PV. Further, this study investigates seasonal variation impacts and associated distribution upgrade costs for a spring season case (March, representing a low load and high PV scenario) and a summer case (July, representing a high load and high PV scenario). Such seasonal analysis will allow system operators to characterize upgrade requirements and associated costs across various periods. Because the spatial distribution of DPV can impact upgrade and associated costs, this study investigates three common DPV deployment scenarios - randomly deployed, close to the substation, and far from the substation - at different penetration levels. Apart from spatial distribution impacts, this project evaluates the techno-economic impacts of the nodal photovoltaic penetration factor (NPPF) for generating the various DPV deployment scenarios at increasing penetration levels. This project investigates the impact of varying nodal PV-to-load ratios using conservative and extreme NPPF values of 3 and 10, respectively. This study investigates the deployment of traditional infrastructure upgrade strategies, such as installing new voltage regulating equipment, transformers and lines replacements, and the activation of advanced inverter functionality (e.g., autonomous volt/VAR) in expanding PV hosting capacity. Existing DPV systems are assumed to operate with the legacy unity power factor, and we considered the possibility of retrofitting such systems with the activation of volt/VAR control as integration standards and regulations continue to evolve to allow such functions. The cost-benefit analysis metrics used in study include distribution upgrade costs, average cost per watt of the upgrade cost, average marginal cost per watt of the upgrade cost, and power losses.

14 SOLAR ENERGY↗

Kernel fusion in atomistic spin dynamics simulations on Nvidia GPUs using tensor core

In atomistic spin dynamics simulations, the time cost of constructing the space- and time-displaced pair correlation function in real space increases quadratically as the number of spins N, leading to significant computational effort. The GEMM subroutine can be adopted to accelerate the calculation of the dynamical spin-spin correlation function, but the computational cost of simulating large spin systems (>40000 spins) on CPUs remains expensive. In this work, we perform the simulation on the graphics processing unit (GPU), a hardware solution widely used as an accelerator for scientific computing and deep learning. Here we show that GPUs can accelerate the simulation up to 25-fold compared to multi-core CPUs when using the GEMM subroutine on both. To hide memory latency, we fuse the element-wise operation into the GEMM kernel using CUTLASS that can improve the performance by 26% ~ 33% compared to implementation based on cuBLAS. Furthermore, we perform the on-the-fly calculation in the epilogue of the GEMM subroutine to avoid saving intermediate results on global memory, which makes the large-scale atomistic spin dynamics simulation feasible and affordable.

97 MATHEMATICS AND COMPUTING↗

Challenging Pneumatic Requirements for Acoustic Testing of the Cryogenic Second Stage for the New Delta 3 Rocket

The paper describes the unique pneumatic test requirements for the acoustic and shock separation testing of the Second Stage for the new Delta III Rocket at the Goddard Space Flight Center in Greenbelt, Maryland. The testing was conducted in the 45,000 cu ft (25-feet wide by 30-feet deep by 50-foot high) Acoustic Facility. The acoustic testing required that the liquid oxygen (LOX) and liquid hydrogen (LH2) tanks be filled with enough liquid nitrogen (LN2) to simulate launch fuel masses during testing. The challenge for this test dealt with designing, procuring, and fabricating the pneumatic supply systems for quick assembly while maintaining the purity requirements and minimizing costs. The pneumatic systems were designed to fill and drain the both LOX and LH2 tanks as well as to operate the fill/drain and vent valves for each of the tanks. The test criteria for the pneumatic sub-systems consisted of function, cleanliness, availability, and cost. The first criteria, function, required the tanks to be filled and drained in an efficient manner while preventing them from seeing pressures greater than 9 psig which would add a pressure cycle to the tank. An LN2 tanker, borrowed from another NASA facility, served as the pre-cool and drain tanker. Pre-cooling the tanks allowed for more efficient and cost effective transfer from the LN2 delivery tankers. Helium gas, supplied from a high purity tube trailer, was used to pressurize the vapor space above the LN2 pushing it into the drain tanker. The tube trailer also supplied high pressure helium to the vehicle for valve control and component purges. Cleanliness was maintained by proper component selection, end-use particle filtration, and any on-site cleaning determined necessary by testing. In order to meet the availability/cost juggling act, products designed for LOX delivery systems were procured to ensure system compatibility while off the shelf valves and tubing designed for the semiconductor industry were procured for the gas systems.

Webb, Andrew T.↗

Evolutionary Telemetry and Command Processor (TCP) architecture

A low cost, modular, high performance, and compact Telemetry and Command Processor (TCP) is being built as the foundation of command and data handling subsystems for the next generation of satellites. The TCP product line will support command and telemetry requirements for small to large spacecraft and from low to high rate data transmission. It is compatible with the latest TDRSS, STDN and SGLS transponders and provides CCSDS protocol communications in addition to standard TDM formats. Its high performance computer provides computing resources for hosted flight software. Layered and modular software provides common services using standardized interfaces to applications thereby enhancing software re-use, transportability, and interoperability. The TCP architecture is based on existing standards, distributed networking, distributed and open system computing, and packet technology. The first TCP application is planned for the 94 SDIO SPAS 3 mission. The architecture enhances rapid tailoring of functions thereby reducing costs and schedules developed for individual spacecraft missions.

Schneider, John R.↗

MEMS Using SOI Substrate

At NASA, the focus for smaller, less costly missions has given impetus for the development of microspacecraft. MicroElectroMechanical System (MEMS) technology advances in the area of sensor, propulsion systems, and instruments, make the notion of a specialized microspacecraft feasible in the immediate future. Similar to the micro-electronics revolution,the emerging MEMS technology offers the integration of recent advances in micromachining and nanofabrication techniques with microelectronics in a mass-producible format,is viewed as the next step in device and instrument miniaturization. MEMS technology offers the potential of enabling or enhancing NASA missions in a variety of ways. This new technology allows the miniaturization of components and systems, where the primary benefit is a reduction in size, mass and power. MEMS technology also provides new capabilities and enhanced performance, where the most significant impact is in performance, regardless of system size. Finally,with the availability of mass-produced, miniature MEMS instrumentation comes the opportunity to rethink our fundamental measurement paradigms. It is now possible to expand our horizons from a single instrument perspective to one involving multi-node distributed systems. In the distributed systems and missions, a new system in which the functionality is enabled through a multiplicity of elements. Further in the future, the integration of electronics, photonics, and micromechanical functionalities into "instruments-on-a-chip" will provide the ultimate size, cost, function, and performance advantage. In this presentation, I will discuss recent development, requirement, and applications of various MEMS technologies and devices for space applications.

Tang, Tony K.↗

RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers

RUSHMAPS is a new onboard data reduction scheme that gives real-time access to key science parameters (e.g. moments) of a class of heliophysics science and/or solar system exploration investigation that includes plasma particle spectrometers (PPS), but requires moments reporting (density, bulk-velocity, temperature, pressure, etc.) of higher-level quality, and tolerates a lowpass (variable quality) spectral representation of the corresponding particle velocity distributions, such that telemetry use is minimized. The proposed methodology trades access to the full-resolution velocity distribution data, saving on telemetry, for real-time access to both the moments and an adjustable-quality (increasing quality increases volume) spectral representation of distribution functions. Traditional onboard data storage and downlink bandwidth constraints severely limit PPS system functionality and drive cost, which, as a consequence, drives a limited data collection and lower angular energy and time resolution. This prototypical system exploit, using high-performance processing technology at GSFC (Goddard Space Flight Center), uses a SpaceCube and/or Maestro-type platform for processing. These processing platforms are currently being used on the International Space Station as a technology demonstration, and work is currently ongoing in a new onboard computation system for the Earth Science missions, but they have never been implemented in heliospheric science or solar system exploration missions. Preliminary analysis confirms that the targeted processor platforms possess the processing resources required for realtime application of these algorithms to the spectrometer data. SpaceCube platforms demonstrate that the target architecture possesses the sort of compact, low-mass/power, radiation-tolerant characteristics needed for flight. These high-performing hybrid systems embed unprecedented amounts of onboard processing power in the CPU (central processing unit), FPGAs (field programmable gate arrays), and DSP (digital signal processing) elements. The fundamental computational algorithm de constructs 3D velocity distributions in terms of spherical harmonic spectral coefficients (which are analogous to a Fourier sine-cosine decomposition), but uses instead spherical harmonics Legendre polynomial orthogonal functions as a basis for the expansion, portraying each 2D angular distribution at every energy or, geometrically, spherical speed-shell swept by the particle spectrometer. Optionally, these spherical harmonic spectral coefficients may be telemetered to the ground. These will provide a smoothed description of the velocity distribution function whose quality will depend on the number of coefficients determined. Successfully implemented on the GSFC-developed processor, the capability to integrate the proposed methodology with both heritage and anticipated future plasma particle spectrometer designs is demonstrated (with sufficiently detailed design analysis to advance TRL) to show specific science relevancy with future HSD (Heliophysics Science Division) solar-interplanetary, planetary missions, sounding rockets and/or CubeSat missions.

Figueroa-Vinas, Adolfo↗

Proposed Project Selection Method for Human Support Research and Technology Development (HSR&TD)

The purpose of HSR&TD is to deliver human support technologies to the Exploration Systems Mission Directorate (ESMD) that will be selected for future missions. This requires identifying promising candidate technologies and advancing them in technology readiness until they are acceptable. HSR&TD must select an may of technology development projects, guide them, and either terminate or continue them, so as to maximize the resulting number of usable advanced human support technologies. This paper proposes an effective project scoring methodology to support managing the HSR&TD project portfolio. Researchers strongly disagree as to what are the best technology project selection methods, or even if there are any proven ones. Technology development is risky and outstanding achievements are rare and unpredictable. There is no simple formula for success. Organizations that are satisfied with their project selection approach typically use a mix of financial, strategic, and scoring methods in an open, established, explicit, formal process. This approach helps to build consensus and develop management insight. It encourages better project proposals by clarifying the desired project attributes. We propose a project scoring technique based on a method previously used in a federal laboratory and supported by recent research. Projects are ranked by their perceived relevance, risk, and return - a new 3 R's. Relevance is the degree to which the project objective supports the HSR&TD goal of developing usable advanced human support technologies. Risk is the estimated probability that the project will achieve its specific objective. Return is the reduction in mission life cycle cost obtained if the project is successful. If the project objective technology performs a new function with no current cost, its return is the estimated cash value of performing the new function. The proposed project selection scoring method includes definitions of the criteria, a project evaluation questionnaire, and a scoring formula.

Jones, Harry↗

Monte Carlo Explicitly Correlated Second-Order Many-Body Green’s Function Calculations of Semiconductor Band Gaps

A systematically converging series of ab initio, post-density-functional, size-consistent, electron-correlated approximations is desired for predictive computing of felectronic band structures of insulating, semiconducting, and metallic solids. A series that meets all of these desiderata (except the applicability to metals) is ab initio many-body Green's function theory based on Gaussian-type-orbital (GTO) basis sets. Here, its leading-order approximation, the second-order Green's function (GF2) method in the diagonal and frequency-independent approximations with the aug-cc-pVDZ basis set, is applied to the fundamental band gaps of three semiconductors (diamond, silicon, and silicon carbide in the zincblende structure) using cluster models. Corrections are made to the basis-set-incompleteness errors by the explicit-correlation (F12) ansatz (GF2-F12) for the valence band edges. The crystals are modeled as surface-passivated clusters of increasing sizes, whose wave functions are expanded by up to 2709 GTO basis functions. Immense computational costs of these calculations are overcome by the highly scalable stochastic algorithm of the Monte Carlo GF2-F12 method, whose operation cost per state increases only as a cubic power of system size, which has a tiny memory footprint and easily achieves near-perfect parallel efficiency on thousands of CPUs or on hundreds of GPUs. The correlated, F12-corrected highest-occupied and lowest-unoccupied molecular-orbital energy (HOMO-LUMO) gap is 5.78 ± 0.07 eV for C 87 H 76 as compared with the experimental value of the fundamental (indirect) band gap of bulk diamond at 5.48 eV. The correlated, F12-corrected HOMO-LUMO gaps for Si 75 H 76 and Si 32 C 43 H 76 are 2.56 ± 0.15 eV and 3.50 ± 0.12 eV, respectively, which are expected to decrease further with increasing cluster sizes. As a result, the experimental fundamental (indirect) band gaps of bulk silicon and silicon carbide are 1.17 eV and 2.42 eV, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Process optimization of complex geometries using feed forward control for laser powder bed fusion additive manufacturing

Additive manufacturing (AM) enables the fabrication of complex designs that are difficult to create by other means. Metal parts manufactured by laser powder bed fusion (LPBF) can incorporate intricate design features and demonstrate desirable mechanical properties. However, printing a part that is qualified for its intended application often involves reprinting and discarding many parts to eliminate defects, improve dimensional accuracy, and increase repeatability. The process of iteratively converging on the appropriate build parameters increases the time and cost of creating functional LPBF manufactured parts. This work describes a fast, scalable method for part-scale process optimization of arbitrary geometries. Additionally, the computational approach uses feature extraction to identify scan vectors in need of parameter adaptation and applies results from simulation-based feed forward control models. This method provides a framework to quickly optimize complex parts through the targeted application of models with a range of fidelity and by automating the transfer of optimization strategies to new part designs. The computational approach and algorithmic framework are described, a software package is implemented, the method is applied to parts with complex features, and parts are printed on a customized open architecture LPBF machine.

3D printing↗

Simultaneous shape and topology optimization of inflatable soft robots

Simultaneous shape and topology optimization is used to design pressure-activated inflatable soft robots. The pressure loaded boundary is meshed conformingly and shape optimized, while the morphology of the robot is topology optimized. The design objective is to exert maximum force on an object, i.e. to produce soft “grippers”. The robot’s motion is modeled using nearly incompressible finite deformation hyperelasticity. To ensure stability of the robot, the buckling load factors obtained via linearized buckling analyses are constrained. The finite element method is used to evaluate the optimization cost and constraint functions and the adjoint method is employed to compute their sensitivities. The numerical examples produce pressure-driven soft robots with varying complexity. We also compare our simultaneous optimization results to those obtained via sequential topology and then shape optimization.

42 ENGINEERING↗

Manufacturing and characterization of continuous fiber-reinforced thermoplastic tape overmolded long fiber thermoplastic

Light-weight construction, design freedom, integration of functions, and compelling cost element are desired by Original Equipment Manufacturers (OEMs) and their suppliers. The emergence of overmolding of continuous-discontinuous reinforcement enables design freedom and ability to tailor stiffness, strength, and damage tolerance for structural applications. In this work, long fiber thermoplastics (LFT) are overmolded with continuous fiber-reinforced thermoplastic (CFRTP) tape are combined using extrusion compression molding process to evaluate the structural performance. The CFRTP tape overmolded LFT samples were characterized using nondestructive and destructive techniques to track fiber alignment, fiber distribution, manufacturing defects, interfacial bonding of the tape – LFT and effect of CFRTP tape on LFT. Mode 1 fracture toughness, G 1c for tape overmolded LFT was higher by 25–30% compared to literature reported G 1c . This response was attributed to excellent fiber distribution, good fiber wetting, and absence of voids at the interface. Three-point bend test indicated that CFRTP tape overmolded LFT composites were better able to resist damage under the bending load compared to constituent LFT composite. Flexural strength of the overmolded composite was higher by 119–142%, and modulus higher by 77–65% compared to constituent LFT composite. Simulated flexural results accurately represents the mechanical behavior of composites. Here, the penetration energy of tape overmolded LFT composites determined by LVI test was in the range of 27.66–30.15 J, which is significantly higher than constituent LFT composite, 7.76 J. CFRTP tape overmolded LFT composite exhibits progressive fiber fracture, matrix cracking, and interfacial debonding failure, whereas, constituent LFT composite showed catastrophic fiber fracture.

42 ENGINEERING↗

Harnessing biomass-derived reinforcements for sustainable flame-resistant composite

Bio-based composites containing natural fiber reinforcements have been integral to developing innovative, low-cost, and low-energy technologies for transportation applications in marine, automotive, and other industries. The low density of natural fibers gives these materials a high specific stiffness and strength, which can lead to significant weight savings in composites. This study focused on a specialty type of wood fiber treated with boric acid (≤ 7%) sourced from Northern White Pine in the USA, marketed as TimberFill. TimberFill is a high aspect ratio, fibrillated wood fiber that is produced commercially for wood fiber insulation; it is chemically treated to improve both its flame retardance and water resistance. In the present study, TimberFill was processed into non-woven mats using a process akin to papermaking and then infiltrated with epoxy resin. Biochar from wood waste was also incorporated into the epoxy resin as a low-cost filler and functional additive. The effects of biochar concentration on composites’ flame retardance (17% improvement in burn rate), thermal conductivity (improved by 9%), and mechanical performance (33% improvement in modulus) are herein presented. Additionally, it explores the plasticizing effect of the boric acid used in the treatment of TimberFill on the thermal and mechanical properties of the resulting composites, specifically on the thermal expansion coefficient.

Joshy, Joslin [ORNL]↗

First principles reactive simulation for equation of state prediction

The high cost of density functional theory (DFT) has hitherto limited the ab initio prediction of the equation of state (EOS). In this article, we employ a combination of large scale computing, advanced simulation techniques, and smart data science strategies to provide an unprecedented ab initio performance analysis of the high explosive pentaerythritol tetranitrate (PETN). Comparison to both experiment and thermochemical predictions reveals important quantitative limitations of DFT for EOS prediction and thus the assessment of high explosives. In particular, we find that DFT predicts the energy of PETN detonation products to be systematically too high relative to the unreacted neat crystalline material, resulting in an underprediction of the detonation velocity, pressure, and temperature at the Chapman–Jouguet state. The energetic bias can be partially accounted for by high-level electronic structure calculations of the product molecules. Furthermore we demonstrate a modeling strategy for mapping chemical composition across a wide parameter space with limited numerical data, the results of which suggest additional molecular species to consider in thermochemical modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling diffusion and depletion in high-aspect-ratio atomic layer deposition processes: Process parameters and manufacturing impacts

Atomic layer deposition (ALD) is a powerful technique for modifying the surface chemistry and properties of substrates with complex and nonplanar topologies. However, achieving uniform and conformal deposition on ultrahigh-aspect-ratio substrates remains challenging, typically requiring large quantities of precursors and long exposure times. Furthermore, process optimization is often performed empirically and involves substantial trial and error. In this work, we perform a combined experimental and computational study of ALD Al 2 O 3 infiltration into silica aerogel monoliths (aspect ratio >10 5 ). A reaction-diffusion model is used to explore the effects of key processing parameters, namely, exposure time per dose, precursor source temperature, number of aerogels in the reactor, and reactor volume. The model is based on quasi-static mode ALD, where the dosed precursor is held in the chamber for a fixed period of time before purging. We analyze the trade-offs between process throughput and precursor utilization for each of these parameters. Furthermore, we investigate the co-optimization and interactions between multiple process parameters, demonstrating the potential for further improvements. Furthermore, this physics-based model can be used to identify a set of process parameters for high-aspect-ratio ALD that meet specific manufacturing objective functions, including throughput, cost, and sustainability.

Aerogel↗

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗