A study of ignition point values of nonmetallic materials in simulated spacecraft environment.
Elastomeric materials thermostability in simulated spacecraft environment tested to obtain ignition point values
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Elastomeric materials thermostability in simulated spacecraft environment tested to obtain ignition point values
Simulated lunar surface material was caused to react with fluorine to determine the feasibility of producing oxygen by this method. The maximum total fluorine pressure used was 53.3 kilonewtons per square meter (400 torr) at temperatures up to 523 K (250 C). Postreaction analysis of both the gas and solid phases indicated that the reaction is feasible but that the efficiency is only about 4 percent of that predicted by theory.
Abstract Dynamic simulation of materials is a promising application for near-term quantum computers. Current algorithms for Hamiltonian simulation, however, produce circuits that grow in depth with increasing simulation time, limiting feasible simulations to short-time dynamics. Here, we present a method for generating circuits that are constant in depth with increasing simulation time for a specific subset of one-dimensional (1D) materials Hamiltonians, thereby enabling simulations out to arbitrarily long times. Furthermore, by removing the effective limit on the number of feasibly simulatable time-steps, the constant-depth circuits enable Trotter error to be made negligibly small by allowing simulations to be broken into arbitrarily many time-steps. For an N -spin system, the constant-depth circuit contains only $\mathcal {O}(N^{2})$ O ( N 2 ) CNOT gates. Such compact circuits enable us to successfully execute long-time dynamic simulation of ubiquitous models, such as the transverse field Ising and XY models, on current quantum hardware for systems of up to 5 qubits without the need for complex error mitigation techniques. Aside from enabling long-time dynamic simulations with minimal Trotter error for a specific subset of 1D Hamiltonians, our constant-depth circuits can advance materials simulations on quantum computers more broadly in a number of indirect ways.
FORTRAN 2 program for computerized simulation of materials handling system
The development of surface technologies for NASA's human and robotic lunar program beyond 2010 has begun. The multitude of projects underway and future ones will soon rely on the availability of lunar regolith simulant materials chosen to simulate the characteristics of lunar regoliths in order to design, test and qualify prototype hardware and flight equipment. The selection and development of standard lunar regolith simulants (SLRS) for the use of NASA technology programs was one of the main recommendations of the 2005 Workshop on Lunar Regolith Simulant Materials at Marshall Space Flight Center. The realization of that objective is now underway through the NASA simulant development program at the Marshall Space Flight Center. The approach adopted to define materials requirements for standard simulants of regolith from the Highlands regions of the Moon will be presented along with a discussion of limitations inherent to such an endeavor.
The paper provides details on the structure and implementation of the Computational Materials program at the NASA Langley Research Center. Examples are given that illustrate the suggested approaches to predicting the behavior and influencing the design of nanostructured materials such as high-performance polymers, composites, and nanotube-reinforced polymers. Primary simulation and measurement methods applicable to multi-scale modeling are outlined. Key challenges including verification and validation of models are highlighted and discussed within the context of NASA's broad mission objectives.
A workshop entitled, Production and Uses of Simulated Lunar Materials, was convened to define the need for simulated lunar materials and examine related issues in support of extended space exploration and development. Lunar samples are a national treasure and cannot be sacrificed in sufficient quantity to test lunar resource utilization process adequately. Hence, the workshop focused on a detailed examination of the variety of potential simulants and the methods for their production.
This Roadmap article provides a succinct, comprehensive overview of the state of electronic structure methods and software for molecular and materials simulations. Seventeen distinct sections collect insights by 51 leading scientists in the field. Each contribution addresses the status of a particular area, as well as current challenges and anticipated future advances, with a particular eye towards software related aspects and providing key references for further reading. Foundational sections cover density functional theory and its implementation in real-world simulation frameworks, Green's function based many-body perturbation theory, wave-function based and stochastic electronic structure approaches, relativistic effects and semiempirical electronic structure theory approaches. Subsequent sections cover nuclear quantum effects, real-time propagation of the electronic structure, challenges for computational spectroscopy simulations, and exploration of complex potential energy surfaces. The final sections summarize practical aspects, including computational workflows for complex simulation tasks, the impact of current and future high-performance computing architectures, software engineering practices, education and training to maintain and broaden the community, as well as the status of and needs for electronic structure based modeling from the vantage point of industry environments. Overall, the field of electronic structure software and method development continues to unlock immense opportunities for future scientific discovery, based on the growing ability of computations to reveal complex phenomena, processes and properties that are determined by the make-up of matter at the atomic scale, with high precision.
Thermal properties of simulated lunar material in air and in vacuum
Thermal properties of simulated lunar materials in air and in a vacuum
Spectral normal emittance of materials under simulated space environment
Due to a paucity of lunar regolith samples, simulated granular materials (simulants) have been developed and deployed for a variety of engineering and research purposes in an attempt to meet the requirements for lunar exploration. Broadly speaking, these manufactured materials aim to replicate the compositional (i.e., mineralogy and chemistry) and physical (e.g., particle size distribution, particle shape) profiles of lunar soil samples collected during the Apollo missions. While creating a “near-perfect” lunar simulant is prohibitive due to the unique formative processes (i.e., meteorite impacts, solar wind implantation) and conditions (anhydrous, reducing environment and exposure to radiation on the surface over billions of years) encountered on the moon, certain granular properties of the regolith can be recreated with a high level of fidelity by leveraging contemporary technologies. A fundamental physical property and descriptor, grain size can be correlated between samples and replicated through processing; however, a holistic understanding of the particle size distribution of lunar regolith must be considered when creating analog materials. This study produces particle size distributions for Apollo 16 returned samples, incorporating the sieved out >1 cm coarse-grained fraction, in order to provide a more comprehensive characterization of surficial lunar regolith grain sizes for the development of highlands-type granular analog testing materials.
Space environment simulator for analysis of spacecraft material reliability during long- duration space mission
Throughout the diverse range of science and engineering applications, there is a growing desire to develop computational methods that can reliably predict the behavior of complex systems. Specifically, there is a strategic need for tools that can robustly forecast the behavior of complex physical systems, where data may be high-dimensional, noisy, or sparse, and models of the system may be time-dependent or include uncertainty. We use mystic to build tools that leverage statistical learning, physics-informed learning, and active learning in the efficient generation of reliably predictive surrogates for complex physical systems. mystic is a robust, proven, open-source optimization and uncertainty quantification toolkit with over a decade of use in the design and optimization of neutron instrumentation, solar-powered drones, and gasguns, and in iterative tuning of models for Raman spectroscopy and elastoplastic materials strength. Recent developments have focused on automated learning of statistically robust surrogates under uncertainty, with applications in materials in extreme environments, nanostructures, materials simulations and strength models, and the failure of shielding under particle radiation. In 2020, McKerns demonstrated active learning of optimally robust surrogates with respect to new simulated data for molecular dynamics simulations of materials mixing in warm dense matter, and is currently applying active learning to the automated steering of particle accelerator beams and the optimal design and control of quantum optical sensor instrumentation.
Commercial interest in advanced reactors for power production in the United States is increasing. A variety of advanced reactor designs are being developed, and many of them use non-traditional fuel forms. Therefore, the material control and accounting (MC&A) methods that will be required for these advanced reactor systems also need to be developed to ensure that the necessary safeguards are implemented. To provide information that can be leveraged to explore different MC&A approaches, three representative advanced reactor types were evaluated from a technical safeguards perspective. These reactor designs were selected to encompass common materials and configurations that could affect safeguards considerations. The three designs evaluated were a molten salt reactor (MSR), a gas-cooled reactor (GCR), and a heat pipe-cooled microreactor.
Resistance to heat penetration and deformations or buckling of three ablation materials during simulated exposure to lifting vehicle afterbody heating
The objectives of this research are to: 1) Investigate the oxidation/ablation behavior of HfB2/SiC materials in simulated re-entry environments; 2) Use the arc jet test results to define appropriate use environments for these materials for use in vehicle design. The parameters to be investigated include: surface temperature, stagnation pressure, duration, number of cycles, and thermal stresses.
Damage in the microstructures of energetic materials (EMs), such as propellants and plastic bonded explosives (PBXs), can significantly alter their response to external loads. Both sensitization and desensitization can occur, causing concerns with safety and performance in the field; predictive models that connect damage and the sensitivity of EMs can enable design and provide confidence in their robustness and reliability. However, modeling of damage evolution is challenging for real microstructures of EMs; samples of damaged EMs are difficult to obtain, thereby hindering experiments and direct numerical simulations to determine the sensitivity of EMs at various stages of damage. Here, we develop an approach to generate synthetic, i.e., in silico produced, damaged microstructures for use in simulations to connect damage levels to sensitivity. The development of the present workflow to generate and impose varying levels of damage in microstructures, known as HEDS (Heterogeneous Energetic Material Damage Simulator), begins with a small set of images of damaged PBXs and combines a collection of deep neural network techniques to generate microstructures with varying levels of damage. By making the synthetic microstructures conform closely to those observed in available real, imaged microstructures, we develop an ensemble of damaged microstructures that can be used for in silico shock experiments. HEDS develops these microstructure ensembles as level set fields, which are directly employed in a sharp interface Eulerian hydrocode where shock simulations are performed to quantify the energy release rate from hotspot fields generated in the microstructure. These capabilities can be useful for the analysis and assessment of changes in the sensitivity of EMs and to design formulations that are less susceptible to damage-induced changes in sensitivity and performance.