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NASA NTRS2012

Human Systems Integration in Practice: Constellation Lessons Learned

NASA's Constellation program provided a unique testbed for Human Systems Integration (HSI) as a fundamental element of the Systems Engineering process. Constellation was the first major program to have HSI mandated by NASA's Human Rating document. Proper HSI is critical to the success of any project that relies on humans to function as operators, maintainers, or controllers of a system. HSI improves mission, system and human performance, significantly reduces lifecycle costs, lowers risk and minimizes re-design. Successful HSI begins with sufficient project schedule dedicated to the generation of human systems requirements, but is by no means solely a requirements management process. A top-down systems engineering process that recognizes throughout the organization, human factors as a technical discipline equal to traditional engineering disciplines with authority for the overall system. This partners with a bottoms-up mechanism for human-centered design and technical issue resolution. The Constellation Human Systems Integration Group (HSIG) was a part of the Systems Engineering and Integration (SE&I) organization within the program office, and existed alongside similar groups such as Flight Performance, Environments & Constraints, and Integrated Loads, Structures and Mechanisms. While the HSIG successfully managed, via influence leadership, a down-and-in Community of Practice to facilitate technical integration and issue resolution, it lacked parallel top-down authority to drive integrated design. This presentation will discuss how HSI was applied to Constellation, the lessons learned and best practices it revealed, and recommendations to future NASA program and project managers. This presentation will discuss how Human Systems Integration (HSI) was applied to NASA's Constellation program, the lessons learned and best practices it revealed, and recommendations to future NASA program and project managers on how to accomplish this critical function.

Zumbado, Jennifer Rochlis↗

DOE OSTI2024

Invariant Molecular Representations for Heterogeneous Catalysis

Catalyst screening is a critical step in the discovery and development of heterogeneous catalysts, which are vital for a wide range of chemical processes. In recent years, computational catalyst screening, primarily through density functional theory (DFT), has gained significant attention as a method for identifying promising catalysts. However, the computation of adsorption energies for all likely chemical intermediates present in complex surface chemistries is computationally intensive and costly due to the expensive nature of these calculations and the intrinsic idiosyncrasies of the methods or data sets used. This study introduces a novel machine learning (ML) method to learn adsorption energies from multiple DFT functionals by using invariant molecular representations (IMRs). To do this, we first extract molecular fingerprints for the reaction intermediates and later use a Siamese-neural-network-based training strategy to learn invariant molecular representations or the IMR across all available functionals. Our Siamese network-based representations demonstrate superior performance in predicting adsorption energies compared with other molecular representations. Notably, when considering mean absolute values of adsorption energies as 0.43 eV (PBE-D3), 0.46 eV (BEEF-vdW), 0.81 eV (RPBE), and 0.37 eV (scan+rVV10), our IMR method has achieved the lowest mean absolute errors (MAEs) of 0.18 0.10, 0.16, and 0.18 eV, respectively. These results emphasize the superior predictive capacity of our Siamese network-based representations. The empirical findings in this study illuminate the efficacy, robustness, and dependability of our proposed ML paradigm in predicting adsorption energies, specifically for propane dehydrogenation on a platinum catalyst surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2011

A Bootstrap Approach to an Affordable Exploration Program

This paper examines the potential to build an affordable sustainable exploration program by adopting an approach that requires investing in technologies that can be used to build a space infrastructure from very modest initial capabilities. Human exploration has had a history of flight programs that have high development and operational costs. Since Apollo, human exploration has had very constrained budgets and they are expected be constrained in the future. Due to their high operations costs it becomes necessary to consider retiring established space facilities in order to move on to the next exploration challenge. This practice may save cost in the near term but it does so by sacrificing part of the program s future architecture. Human exploration also has a history of sacrificing fully functional flight hardware to achieve mission objectives. An affordable exploration program cannot be built when it involves billions of dollars of discarded space flight hardware, instead, the program must emphasize preserving its high value space assets and building a suitable permanent infrastructure. Further this infrastructure must reduce operational and logistics cost. The paper examines the importance of achieving a high level of logistics independence by minimizing resource consumption, minimizing the dependency on external logistics, and maximizing the utility of resources available. The approach involves the development and deployment of a core suite of technologies that have minimum initial needs yet are able expand upon initial capability in an incremental bootstrap fashion. The bootstrap approach incrementally creates an infrastructure that grows and becomes self sustaining and eventually begins producing the energy, products and consumable propellants that support human exploration. The bootstrap technologies involve new methods of delivering and manipulating energy and materials. These technologies will exploit the space environment, minimize dependencies, and minimize the need for imported resources. They will provide the widest range of utility in a resource scarce environment and pave the way to an affordable exploration program.

Oeftering, Richard C.↗

DOE OSTI2023

Deep Learning Potential For Investigation of Chemical Conversion of CO2 at Air-Reactive Deep Eutectic Solvent Interface

Capturing CO2 from air is urgent to battle against the climate change. Traditional CO2 capture by alkaline solution or aqueous amine has high regeneration cost, equipment corrosion, and amine leakage. Deep eutectic solvents (DESs) are promising alternatives with low corrosion, non-toxicity, and biodegradable nature. Functionalized DESs can capture and convert CO2 at low partial pressures. Developing reactive DESs for efficient CO2 capture needs a foundational understanding of the reaction-transport coupling of CO2 at the air-DES interface. In this study, we develop a deep learning potential (DLP) to investigate the absorption and reaction of CO2 at the air-DES interface (DES: 1-ethyl-3-methylimidazolium 2-cyanopyrrolide ([Emim][2-CNpyr]) and ethylene glycol (EG)). The DLP model allows us to simulate chemical reactions at a lower computational cost with ab initio accuracy. By analyzing reaction free energy surfaces, molecular interactions among CO2, DES components and reaction products, and transport of CO2 through the interface, we identify three main reaction pathways of CO2 at the interface: forming carboxylate with [Emim], carbamate with [2-CNpyr], and carbonate with EG. The mechanistic understanding of CO2 chemisorption at the interface will facilitate the development of novel direct air capture technology using DESs.

Nguyen, Manh Tien↗

DOE OSTI2022

Modified Calcium Manganites for Thermochemical Energy Storage Applications

CaAl 0.2 Mn 0.8 O 3-δ (CAM28) and CaTi 0.2 Mn 0.8 O 3-δ (CTM28) are perovskite metal oxides developed for high-temperature thermochemical energy storage (TCES) applications, e.g., in support of air Brayton power generation. Previous reports for these compounds focus on the equilibrium non-stoichiometry (δ) as a function of temperature and oxygen partial pressure (pO 2 ) and the endotherm (or exotherm) accompanying changes in δ resulting from thermal reduction (or re-oxidation). Herein, we report results for elemental substitution and doping (Al, Co, Fe, La, Sr, Ti, Y, Zn, and Zr) of calcium manganites (CM) that establish the preference for CAM28 and CTM28. Techniques employed include conventional (screening and equilibrium) and ballistically heated multi-cycle thermogravimetric analysis (TGA), conventional and high temperature ( in-situ ) X-ray diffraction (XRD), and differential scanning calorimetry (DSC). Forward-looking results for A-site Y-doped materials, e.g., Ca 0.9 Y 0.1 MnO 3-δ (CYM910), establish a route to increasing the reduction enthalpy relative to CAM28 and CTM28, albeit at the expense of increased reduction temperatures and raw materials costs. A thermodynamic model presented for CAM28, but extendable to related materials, provides values for the reaction enthalpy and extent of reduction as a function of temperature and oxygen partial pressure for use in design efforts. Taken as a whole, the results support the choice of Al-doped CaMnO 3-δ as a low-cost material for TCES in a high temperature air Brayton application, but point the way to achieving higher stored energy densities that could lead to overall cost savings.

Miller, James E.↗

DOE OSTI2025

Calibration of RAFM Micromechanical Model for Creep Using Bayesian Optimization for Functional Output

A Bayesian optimization procedure is presented for calibrating a multimechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based on Fe(8–9)%Cr are the most promising candidates for some fusion reactor structures. Although there are indications that RAFM steel could be viable for fusion applications at temperatures up to 600°C, the maximum operating temperature will be determined by the creep properties of the structural material and the breeder material compatibility with the structural material. Due to the relative paucity of available creep data on F82H steel compared to other alloys such as Grade 91 steel, micromechanical models are sought for simulating creep based on relevant deformation mechanisms. As a point of departure, this work recalibrates a model form that was previously proposed for Grade 91 steel to match creep curves for F82H steel. Due to the large number of parameters (9) and cost of the nonlinear simulations, an automated approach for tuning the parameters is pursued using a recently developed Bayesian optimization for functional output (BOFO) framework (Huang et al., 2021, “Bayesian optimization of functional output in inverse problems,” Optim. Eng., 22, pp. 2553–2574). Incorporating extensions such as batch sequencing and weighted experimental load cases into BOFO, a reasonably small error between experimental and simulated creep curves at two load levels is achieved in a reasonable number of iterations. In conclusion, validation with an additional creep curve provides confidence in the fitted parameters obtained from the automated calibration procedure to describe the creep behavior of F82H steel.

42 ENGINEERING↗

DOE OSTI2025

Accelerating high-order continuum kinetic plasma simulations using multiple GPUs

Kinetic plasma simulations solve the Vlasov-Poisson or Vlasov-Maxwell equations to evolve scalar-variable distribution functions in position-velocity phase space and vector-variable electromagnetic fields in configuration space. The immense computational cost of evolving high-dimensional variables, and their large number of degrees of freedom, often limits the utility of continuum kinetic simulations and presents a challenge when it comes to accurately simulating real-world physical phenomena. To address this challenge, we present techniques that accelerate and minimize the computational work required for a scalable Vlasov-Poisson solver. We show theoretical hardware compute and communication bounds for solving a fourth-order finite-volume Vlasov-Poisson system. These bounds are then used to inform and evaluate the design of performance portable algorithms for a multiple graphics processing unit (GPU) accelerated version of the Vlasov-Poisson solver VCK-CPU [1]. We demonstrate that the multi-GPU Vlasov solver implementation, VCK-GPU, simultaneously minimizes required inter-process data transfer while also being bounded by the machine network performance limits. This results in an overall strong scaling speedup per timestep of up to 40x in three-dimensional phase space (one position, two velocity coordinates) and 54x in four dimensional phase space (two position, two velocity coordinates) and a 341x increase in simulation throughput of the GPU accelerated code over the existing CPU code. The GPU code is also able to weak scale up to 256 compute nodes and 1024 GPUs. In conclusion, we demonstrate that the improved compute performance enables exploring configurations which were previously computationally infeasible, including resolving fine-scale distribution function filamentation and multi-species dynamics with realistic electron-proton mass ratios.

Continuum kinetics↗

DOE OSTI2026

Ab initio calculation of atomic solid hydrogen phases based on Gutzwiller many-body wave functions

We apply two ab initio many-body methods based on Gutzwiller wave functions, i.e., correlation matrix renormalization theory (CMRT) and Gutzwiller conjugate gradient minimization (GCGM), to the study of crystalline phases of atomic hydrogen. Both methods avoid empirical Hubbard U parameters and are free from double-counting issues. CMRT employs a Gutzwiller-type approximation that enables efficient calculations, while GCGM goes beyond this approximation to achieve higher accuracy at higher computational cost. By benchmarking against available quantum Monte Carlo (QMC) results, we demonstrate that while both methods are more accurate than the widely used density-functional theory, GCGM systematically captures additional correlation energy missing in CMRT, leading to significantly improved total energy predictions. We also show that by including the correlation energy Ec from local density approximation in the CMRT calculation, CMRT + E c produces energy in better agreement with the QMC results in these hydrogen lattice systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Commercial building HVAC demand flexibility with model predictive control: Field demonstration and literature insights

Model Predictive Control (MPC) for building Heating Ventilation and Air Conditioning (HVAC) systems is beginning to gain traction in the market, with a few controls companies incorporating it into their product offerings. However, it remains difficult to assess whether the energy cost savings are enough to justify the cost of MPC implementation for a particular building, given the limited number of reported demonstrations. For small commercial and residential buildings with relatively uniform systems, standardized approaches can help lower implementation costs. In contrast, for large buildings or district systems, the potential magnitude of cost savings could justify more customized solutions. Estimating the cost-effectiveness of MPC becomes more challenging for medium and large commercial buildings, where a one-size-fits-all solution may not be suitable, and the potential energy cost savings may be insufficient to justify a customized solution. To make MPC technology more appealing, incorporating additional value streams beyond energy efficiency alone can significantly increase its attractiveness. One such revenue stream is demand flexibility, in response to dynamic electricity prices, where MPC can leverage the thermal mass of the building to shift the load and support the grid. Building on an extensive literature review of MPC field studies focused on cost savings and demand flexibility, this paper presents the results of implementing MPC control in a large office building HVAC system in Berkeley, CA. Four different dynamic electricity price profiles were integrated into the MPC objective function to shift building demand while maintaining comfort, and field testing was performed with each price profile across four seasons. The results show potential for 40–65 % demand decrease percentage and up to 61 % annual cost savings compared to the existing rule-based control strategy, under the tested dynamic price scenarios. This paper also presents a sensitivity analysis on the cost savings with respect to the price profile variability, discusses the implementation effort for the price-responsive MPC, and compares the cost savings found in this study to those found in literature on the basis of dynamic price variability, or so-called Electricity Price Relative Standard Deviation.

Zanetti, Ettore↗

DOE OSTI2022

Weight function procedure for reduced order fracture analysis of arbitrary flaws in cylindrical pressure vessels

Fracture mechanics calculations using the finite element method can be computationally expensive, which makes them challenging to use in engineering evaluations of flaws in pressure vessels. The weight function (WF) technique is a reduced order fracture modeling method that is widely used to greatly reduce these computational costs. Its computational efficiency is essential for use in probabilistic fracture mechanics evaluations of embrittled nuclear reactor pressure vessels (RPVs), due to the large number of sampled flaws that must be evaluated. Although the WF technique is general, it is typically used only for axis-aligned flaws. Recent discoveries of off-axis flaws in operating nuclear reactors have necessitated detailed simulations of such flaws and the interactions between neighboring flaws. This paper presents a generalized WF approach applicable for analyzing arbitrary flaw geometries in thick-walled cylindrical vessels, including surface-breaking and subsurface flaws, which can either axis-aligned or off-axis, and can account for interactions with other flaws. Herein, this approach is demonstrated on representative simulations of multiple flaw geometries in a RPV subjected to transient loading conditions. In all cases, the WF technique gives good comparison with benchmark results from direct simulation with greatly reduced computational effort.

42 ENGINEERING↗

NASA NTRS1976

Zonal and tesseral harmonic coefficients for the geopotential function, from zero to 18th order

Zonal and tesseral harmonic coefficients for the geopotential function are usually tabulated in normalized form to provide immediate information as to the relative significance of the coefficients in the gravity model. The normalized form of the geopotential coefficients cannot be used for computational purposes unless the gravity model has been modified to receive them. This modification is usually not done because the absolute or unnormalized form of the coefficients can be obtained from the simple mathematical relationship that relates the two forms. This computation can be quite tedious for hand calculation, especially for the higher order terms, and can be costly in terms of storage and execution time for machine computation. In this report, zonal and tesseral harmonic coefficients for the geopotential function are tabulated in absolute or unnormalized form. The report is designed to be used as a ready reference for both hand and machine calculation to save the user time and effort.

Kirkpatrick, J. C.↗

DOE OSTI2022

Multi-objective optimization of root phenotypes for nutrient capture using evolutionary algorithms

Root phenotypes are avenues to the development of crop cultivars with improved nutrient capture, which is an important goal for global agriculture. The fitness landscape of root phenotypes is highly complex and multidimensional. It is difficult to predict which combinations of traits (phene states) will create the best performing integrated phenotypes in various environments. Brute force methods to map the fitness landscape by simulating millions of phenotypes in multiple environments are computationally challenging. Evolutionary optimization algorithms may provide more efficient avenues to explore high dimensional domains such as the root phenotypic space. We coupled the three-dimensional functional–structural plant model, SimRoot, to the Borg Multi-Objective Evolutionary Algorithm (MOEA) and the evolutionary search over several generations facilitated the identification of optimal root phenotypes balancing trade-offs across nutrient uptake, biomass accumulation, and root carbon costs in environments varying in nutrient availability. Our results show that several combinations of root phenes generate optimal integrated phenotypes where performance in one objective comes at the cost of reduced performance in one or more of the remaining objectives, and such combinations differed for mobile and non-mobile nutrients and for maize (a monocot) and bean (a dicot). Functional–structural plant models can be used with multi-objective optimization to identify optimal root phenotypes under various environments, including future climate scenarios, which will be useful in developing the more resilient, efficient crops urgently needed in global agriculture.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Enabling Large-Scale Condensed-Phase Hybrid Density Functional Theory Based Ab Initio Molecular Dynamics. 1. Theory, Algorithm, and Performance

By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semilocal density functional theory (DFT) and thereby furnish a more accurate and reliable description of the underlying electronic structure in systems throughout biology, chemistry, physics, and materials science. However, the high computational cost associated with the evaluation of all required EXX quantities has limited the applicability of hybrid DFT in the treatment of large molecules and complex condensed-phase materials. To overcome this limitation, we describe a linear-scaling approach that utilizes a local representation of the occupied orbitals (e.g., maximally localized Wannier functions (MLWFs)) to exploit the sparsity in the real-space evaluation of the quantum mechanical exchange interaction in finite-gap systems. In this work, we present a detailed description of the theoretical and algorithmic advances required to perform MLWF-based ab initio molecular dynamics (AIMD) simulations of large-scale condensed-phase systems of interest at the hybrid DFT level. We focus our theoretical discussion on the integration of this approach into the framework of Car–Parrinello AIMD, and highlight the central role played by the MLWF-product potential (i.e., the solution of Poisson’s equation for each corresponding MLWF-product density) in the evaluation of the EXX energy and wave function forces. We then provide a comprehensive description of the exx algorithm implemented in the open-source Quantum ESPRESSO program, which employs a hybrid MPI/OpenMP parallelization scheme to efficiently utilize the high-performance computing (HPC) resources available on current- and next-generation supercomputer architectures. Furthermore, this is followed by a critical assessment of the accuracy and parallel performance (e.g., strong and weak scaling) of this approach when AIMD simulations of liquid water are performed in the canonical (NVT) ensemble. With access to HPC resources, we demonstrate that exx enables hybrid DFT-based AIMD simulations of condensed-phase systems containing 500–1000 atoms (e.g., (H₂O)₂₅₆) with a wall time cost that is comparable to that of semilocal DFT. In doing so, exx takes us one step closer to routinely performing AIMD simulations of complex and large-scale condensed-phase systems for sufficiently long time scales at the hybrid DFT level of theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1974

Space processing applications payload equipment study. Volume 2E: Commercial equipment utility

Examination of commercial equipment technologies revealed that the functional performance requirements of space processing equipment could generally be met by state-of-the-art design practices. Thus, an apparatus could be evolved from a standard item or derived by custom design using present technologies. About 15 percent of the equipment needed has no analogous commercial base of derivation and requires special development. This equipment is involved primarily with contactless heating and position control. The derivation of payloads using commercial equipment sources provides a broad and potentially cost-effective base upon which to draw. The derivation of payload equipment from commercial technologies poses other issues beyond that of the identifiable functional performance, but preliminary results on testing of selected equipment testing appear quite favorable. During this phase of the SPA study, several aspects of commercial equipment utility were assessed and considered. These included safety, packaging and structural, power conditioning (electrical/electronic), thermal and materials of construction.

Smith, A. G.↗

NASA NTRS1993

Using magnetic tape technology for data migration

Magnetic tape and optical disk library units (jukeboxes) are satisfying the demand for high-capacity cost-effective storage. The choice between optical disk and magnetic tape technology must take into account the cost limitations as well as the performance and reliability requirements of the user environment. Library units require data management software in order to function in an automated and user-transparent way. The most common data management applications are backup and recovery, data migration, and archiving. The medium access patterns that these applications create will be described. Since the most user visible application is data migration, a queue simulator was developed to model its performance against a variety of library units. The major subject of this paper is the design and implementation of this simulator as well as some simulation results. The relative cost and reliability of magnetic tape versus optical disk library units is presented for completeness.

Therrien, David↗

NASA NTRS2019

Transfer-Function Determination for Infinite-Tube-Probe Pressure Transducers with Application to Turbofan Core/Combustor Noise

Turbofan hot-section unsteady pressure measurements are complicated by environmental limitations of current-generation sensors. Accurate direct measurements are normally not possible and engine-external measurement techniques, using sufficiently long sense lines, are utilized instead. Remote measurement comes at a cost, however, as it introduces a magnitude reduction within the line as well as a phase lag relative to the desired engine-internal measurement location. Determination, or validation, of a transfer function relating the engine internal pressure to the observed remote value is necessary. Transfer functions are examined for various configurations of the so-called infinite-tube-probe arrangement in order to optimize measurement performance. The experimental setup uses a normal-incidence tube that ordinarily is utilized for impedance eduction. Here, its downstream end instead is made up of a hard-wall termination instrumented with a flush-mounted microphone and a Kulite pressure transducer as well as a sense line connection. This allows the remote and direct measurements to be related under controlled conditions. Transfer-function measurements are presented and compared to predictions for several parametric variations.

Combustor Noise↗

NASA NTRS2019

Transfer-Function Determination for Infinite-Tube-Probe Pressure Transducers with Application to Turbofan Core/Combuster Noise

Turbomachinery Noise↗

NASA NTRS1983

Analysis of structural perturbations in systems via cost decomposition methods

It has long been common practice to analyze linear dynamic systems by decomposing the total response in terms of individual contributions which are easier to analyze. Examples of this philosophy include the expansion of transfer functions using: (1) the superposition principle, (2) residue theory and partial fraction expansions, (3) Markov parameters, Hankel matrices, and (4) regular and singular perturbations. This paper summarizes a new and different kind of expansion designed to decompose the norm of the response vector rather than the response vector itself. This is referred to as "cost-decomposition' of the system. The notable advantages of this type of decomposition are: (a) easy application to multi-input, multi-output systems, (b) natural compatibility with Linear Quadratic Gaussian Theory, (c) applicability to the analysis of more general types of structural perturbations involving inputs, outputs, states, parameters. Property (c) makes the method suitable for problems in model reduction, measurement/actuator selections, and sensitivity analysis.

Skelton, R. E.↗

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