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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Fluid-Thermal-Structural Interactions Induced by an Asymmetric Shock-Wave/Boundary-Layer Interaction in a Mach-6 Compression Corner

An experimental study is conducted of the fluid-thermal-structural interaction of a clamped compliant panel exposed to a three dimensional shock-wave/boundary-layer interaction (SWBLI) induced by a Mach-6 compression ramp with a spanwise nonuniform incoming boundary layer. The nonuniform boundary layer was produced by placing trips on one side of the upstream flat plate, resulting in largely turbulent flow on the tripped side and transitional flow on the untripped side. Measurements of the flowfield confirmed that the tripped boundary layer contained elevated levels of unsteadiness, and the SWBLI was observed to vary from attached to fully separated as the ramp angle was increased from 10◦ to 38◦; the separation region on the tripped side of the panel was noticeably smaller, showing the elevated turbulence levels of the tripped-side flow to remain relatively localized rather than diffusing across the whole model. Full-field, time-resolved panel deformations were measured using high-speed photogrammetry and the vibrational response at each compression angle was characterized. Although the measured modes conformed largely to those from classical clamped-plate theory, some skewing of the mode shapes was observed. IR thermography highlighted regions of the compliant region where elevated temperatures were likely to promote thermal softening effects to the transient panel response. The quasi-static deformation and stress field was used to characterize the internal stress factor of each mode and showed a meaningful relationship between transient panel response and stress contained within each mode: modes with antinodes lying in high-stress areas of the plate tended to exhibit increases in vibrational frequency and decreases in vibrational power, whereas the opposite was true for modes with antinodes in low-stress areas.

Spectral Proper Orthogonal Decomposition↗
NASA NTRS1996

Development of Multiobjective Optimization Techniques for Sonic Boom Minimization

A discrete, semi-analytical sensitivity analysis procedure has been developed for calculating aerodynamic design sensitivities. The sensitivities of the flow variables and the grid coordinates are numerically calculated using direct differentiation of the respective discretized governing equations. The sensitivity analysis techniques are adapted within a parabolized Navier Stokes equations solver. Aerodynamic design sensitivities for high speed wing-body configurations are calculated using the semi-analytical sensitivity analysis procedures. Representative results obtained compare well with those obtained using the finite difference approach and establish the computational efficiency and accuracy of the semi-analytical procedures. Multidisciplinary design optimization procedures have been developed for aerospace applications namely, gas turbine blades and high speed wing-body configurations. In complex applications, the coupled optimization problems are decomposed into sublevels using multilevel decomposition techniques. In cases with multiple objective functions, formal multiobjective formulation such as the Kreisselmeier-Steinhauser function approach and the modified global criteria approach have been used. Nonlinear programming techniques for continuous design variables and a hybrid optimization technique, based on a simulated annealing algorithm, for discrete design variables have been used for solving the optimization problems. The optimization procedure for gas turbine blades improves the aerodynamic and heat transfer characteristics of the blades. The two-dimensional, blade-to-blade aerodynamic analysis is performed using a panel code. The blade heat transfer analysis is performed using an in-house developed finite element procedure. The optimization procedure yields blade shapes with significantly improved velocity and temperature distributions. The multidisciplinary design optimization procedures for high speed wing-body configurations simultaneously improve the aerodynamic, the sonic boom and the structural characteristics of the aircraft. The flow solution is obtained using a comprehensive parabolized Navier Stokes solver. Sonic boom analysis is performed using an extrapolation procedure. The aircraft wing load carrying member is modeled as either an isotropic or a composite box beam. The isotropic box beam is analyzed using thin wall theory. The composite box beam is analyzed using a finite element procedure. The developed optimization procedures yield significant improvements in all the performance criteria and provide interesting design trade-offs. The semi-analytical sensitivity analysis techniques offer significant computational savings and allow the use of comprehensive analysis procedures within design optimization studies.

Chattopadhyay, Aditi↗
NASA NTRS2004

Adjoint Algorithm for CAD-Based Shape Optimization Using a Cartesian Method

Adjoint solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape optimization. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (geometric parameters that control the shape). More recently, emerging adjoint applications focus on the analysis problem, where the adjoint solution is used to drive mesh adaptation, as well as to provide estimates of functional error bounds and corrections. The attractive feature of this approach is that the mesh-adaptation procedure targets a specific functional, thereby localizing the mesh refinement and reducing computational cost. Our focus is on the development of adjoint-based optimization techniques for a Cartesian method with embedded boundaries.12 In contrast t o implementations on structured and unstructured grids, Cartesian methods decouple the surface discretization from the volume mesh. This feature makes Cartesian methods well suited for the automated analysis of complex geometry problems, and consequently a promising approach to aerodynamic optimization. Melvin et developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the Euler equations. In both approaches, a boundary condition is introduced to approximate the effects of the evolving surface shape that results in accurate gradient computation. Central to automated shape optimization algorithms is the issue of geometry modeling and control. The need to optimize complex, "real-life" geometry provides a strong incentive for the use of parametric-CAD systems within the optimization procedure. In previous work, we presented an effective optimization framework that incorporates a direct-CAD interface. In this work, we enhance the capabilities of this framework with efficient gradient computations using the discrete adjoint method. We present details of the adjoint numerical implementation, which reuses the domain decomposition, multigrid, and time-marching schemes of the flow solver. Furthermore, we explain and demonstrate the use of CAD in conjunction with the Cartesian adjoint approach. The final paper will contain a number of complex geometry, industrially relevant examples with many design variables to demonstrate the effectiveness of the adjoint method on Cartesian meshes.

Nemec, Marian↗
DOE OSTI2024

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Modeling Personnel Turnover in the Parametric Organization

A primary issue in organizing a new parametric cost analysis function is to determine the skill mix and number of personnel required. The skill mix can be obtained by a functional decomposition of the tasks required within the organization and a matrixed correlation with educational or experience backgrounds. The number of personnel is a function of the skills required to cover all tasks, personnel skill background and cross training, the intensity of the workload for each task, migration through various tasks by personnel along a career path, personnel hiring limitations imposed by management and the applicant marketplace, personnel training limitations imposed by management and personnel capability, and the rate at which personnel leave the organization for whatever reason. Faced with the task of relating all of these organizational facets in order to grow a parametric cost analysis (PCA) organization from scratch, it was decided that a dynamic model was required in order to account for the obvious dynamics of the forming organization. The challenge was to create such a simple model which would be credible during all phases of organizational development. The model development process was broken down into the activities of determining the tasks required for PCA, determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the dynamic model, implementing the dynamic model, and testing the dynamic model.

Dean, Edwin B.↗
NASA NTRS2003

Temporal Evolution of Nanostructures in a Model Nickel-Base Superalloy: Experiments and Simulations

The temporal evolution of the nanostructure of a model Ni-base superalloy (Ni-5.2 at.% Al-14.2 at.% Cr) is studied experimentally employing three-dimensional atom-probe (3DAP) microscopy in conjunction with kinetic Monte Carlo (KMC) simulations at 600 C. It is demonstrated that not only can the mean compositions of individual gamma' (Ni3Al with the Li2 structure) precipitates be measured but the Ni, Al, and Cr concentration profiles within the precipitates can also be determined for precipitates with a mean radius ( ) as small as 0.85 nm. The three asymptotic tinie dependencies of the Lifshitz-Slyzov-Wagner (LSW) theory of coarsening (Ostwald ripening) are measured and found to deviate from its theoretical predictions: possible explanations for these discrepancies are discussed. At 0.25 hr. there is 3DAP microscope evidence for the presence of precipitates of another nickel-rich phase. ="Ni3Cr" (Ni3Cr(1-x)Al(x)), which exhibits short-range order (SRO) and that is metastable with respect to Ni3Al. This metastable phase is also found by KMC simulations and has the composition Ni3Cr(1-x)Al(x), which is Ni-2.91 at.% Al-21.98 at.% Cr at 16 hours. Our results demonstrate that the decomposition of gamma the primary gamma (FCC) phase results in the concurrent formation of an ordered phase and a disordered phase by 0.25 hours.

Sudbrack, Chantal K.↗
DOE OSTI2024

Decomposition and Algorithmic Approaches for Solving Large-Scale Process Family Design Problems

Our most recent work expands the water desalination case study from 76 variants to 10,897 variants using the equation-oriented model built in Pyomo as part of the PARETO project. Using the discretization formulation presented in Stinchfield (2024a), rather than solving for all 10,897 variants simultaneously, we decompose the formulation into subproblems containing subsets of variants from the process family. We solve the overall problem with Progressive Hedging (PH) deployed in parallel on a distributed HPC cluster using the open-source Python package mpi-sppy (Knueven et al., 2023). This approach allowed us to solve this process family design problem to ~1.5% relative optimality gap in about 5 hours; in comparison, Gurobi reached ~50% relative optimality gap in about 6 hours (Stinchfield et al., 2024b). However, this approach still requires discretization of the common unit module design ranges; additionally, PH acts as a heuristic for MILP’s with gap-closing capabilities. Ideally, we would not have to use ML surrogates or discretization to solve this problem, instead solving the process family design problem with the equation-oriented model directly to achieve the most accurate results. However, recall that we did not consider solving the MINLP directly due to complexity and size. In this work, we aim to decompose and solve this large-scale MINLP using a Structured Nonlinear Global Optimization algorithm presented by Cao and Zavala (2019).

Stinchfield, Georgia↗
DOE OSTI2025

Beyond real: alternative unitary cluster Jastrow models for molecular electronic structure calculations on near-term quantum computers

Near-term quantum devices require wavefunction ansätze that are expressive while also of shallow circuit depth in order to both accurately and efficiently simulate molecular electronic structure. While the unitary coupled cluster ansatz (e.g., UCCSD) has become a standard, the high gate count associated with the implementation of this limits its feasibility on noisy intermediate-scale quantum (NISQ) hardware. k -Fold unitary cluster Jastrow (uCJ) ansätze mitigate this challenge by providing O( kN 2 ) circuit scaling and favorable linear depth circuit implementation. Previous work has focused on the real orbitalrotation (Re-uCJ) variant of uCJ, which allows an exact (Trotter-free) implementation. Here we extend and generalize the k -fold uCJ framework by introducing two new variants, Im-uCJ and g-uCJ, which incorporate imaginary and fully complex orbital rotation operators, respectively. Similar to Re-uCJ, both of the new variants achieve quadratic gate-count scaling. Our results focus on the simplest k = 1 model, and show that the uCJ models frequently maintain energy errors within chemical accuracy (∼1 kcal mol −1 ). Both g-uCJ and Im-uCJ are more expressive in terms of capturing electron correlation and are also more accurate than the earlier Re-uCJ ansatz. We further show that Im-uCJ and g-uCJ circuits can also be implemented exactly, without any Trotter decomposition. Numerical tests using k = 1 on H 2 , H 3 + , Be 2 , C 2 H 4 , C 2 H 6 and C 6 H 6 in various basis sets confirm the practical feasibility of these shallow Jastrow-based ansätze for applications on near-term quantum hardware.

Tkachenko, Nikolay V. [University of California, B↗
NASA NTRS1999

Data Structure and Parallel Decomposition Considerations on a Fibonacci Grid

The Fibonacci grid, proposed by Swinbank and Purser (see companion abstract), provides attractive properties for global numerical atmospheric prediction by offering an optimally homogeneous, geometrically regular, and approximately isotropic discretization, with only the polar regions requiring special numerical treatment. It is a mathematical idealization, applied to the sphere, of the multi-spiral patterns often found in botanical structures, such as in pine cones and sunflower heads. Computationally, it is natural to organize the domain, into zones, in each of which the same pair, or triple, of "Fibonacci spirals" dominate. But the further subdivision of such zones into "tiles" of a shape and size suitable for distribution to the processors of a massively parallel computer requires very careful consideration if the subsequent spatial computations along the respective spirals, especially those computations (such as compact differencing schemes) that involve recursion, can be implemented in an efficient "load-balanced "manner without requiring excessive amounts of inter-processor communications. In this paper we show how certain "number theoretic" properties of the Fibonacci sequence (whose numbers prescribe the multiplicity of successive spirals) may be exploited in the decomposition of grid zones into tidy arrangements of triangular grid tiles, each tile possessing one side approximately parallel to the constant-latitude zone boundary. We also describe how the spatially recursive processes may be decomposed across such a tiling, and the directionality of the recursions reversed on alternate grid lines, to ensure a very high degree of load balancing throughout the execution of the computations required for one time step of a global model.

Michalakes, John↗
NASA NTRSDate not supplied

Surface-Normal Active Flow Control for Lift Enhancement and Separation Mitigation for High-Lift Common Research Model

This study explores the feasibility of using small surface-normal jets near the flap trailing edge as active aerodynamic load control on the high-lift Common Research Model wing/-body configuration. Chimera Grid Tools are utilized to generate structured curvilinear overset grids, and the Reynolds-averaged Navier-Stokes solver OVERFLOW is employed to solve for the flow-field around the geometry. The so-called microjet is initially employed across both the inboard and the outboard flaps on the pressure-side near the trailing edge. It is shown that implementing the microjet on the inboard flap is more effective compared to implementing it on the outboard flap. This is because, prior to microjet implementation, the flow on the outboard flap exhibits extensive separation, while the flow on the inboard flap exhibits moderate separation. For microjet implementation across the inboard flap only, the relationship between momentum coefficient of the microjet and lift-enhancement is found to be∆CL'1.66√Cμfor the rangeCμ= 0.00−0.012. We show that implementing a microjet with a jet velocity ratio of one, which corresponds toCμ= 0.003, can shift the linear region of the lift curve by ∆CL= 0.08. The linear shift in the lift curve is significant for enhancing airplane performance such as increasing its payload. Microjet implementation effects on the drag coefficient are also investigated through a drag decomposition analysis. Further, we employ an induced drag analysis based on the spanwise load distribution and show that the microjet-related increase in pressure drag coefficient is dominated by the increase in the induced drag while microjet implementation reduces the form drag. These preliminary results show that favorable changes in aerodynamic performance can be achieved by using the surface-normal jets presented in this study.

ARMD↗
NASA NTRS2004

Computational and Experimental Study of Energetic Materials in a Counterflow Microgravity Environment

Counterflow diffusion flames are studied for various fuels flowing against decomposition products from solid ammonium perchlorate (AP) pellets in order to obtain fundamental understanding of composite propellant flame structure and chemistry. We illustrate this approach through a combined experimental and numerical study of a fuel mixture consisting of C2H4 CO + H2, and C2H2 + C2H4 flowing against solid AP. For these particular AP-fuel systems, the resulting flame zone simulates the various flame structures that are ex+ to exist between reaction products from Ap crystals and a hydrocarbon binder. As in all our experimental studies, quantitative species and temperature profiles have been measured between the fuel exit and AP surface. Species measured included CN, NH, NO, OH, N2, CO2, CO, H2, CO, HCl, and H2O. Temperature was measured using a thermocouple at the exit, spontaneous Raman scattering measurements throughout the flame, OH rotational population distributions, and NO vibrational population distributions. The burning rate of AP was also measured as a function of strain rate, given by the separation distance between the AP surface and the gaseous hydrocarbon fuel tube exit plane. This distance was nominally set at 5 mm, although studies have been performed for variations in separation distance. The measured 12 scalars are compared with predictions from a detailed gas-phase kinetics model consisting of 86 species and 531 reactions. Model predictions are found to be in good agreement with experiment and illustrate the type of kinetic features that may be expected to occur in propellants when AP particle size distributions are varied. Furthermore, the results constitute the continued development of a necessary database and validation of a comprehensive model for studying more complex AP-solid fuel systems in microgravity. Exploratory studies have also been performed with liquid and solid fuels at normal gravity. Because of melting (and hence dripping) and deep thermal wave penetration into the liquid, these experiments were found feasible, but not used for obtaining quantitative data. Microgravity experiments are needed to eliminate the dripping and boiling phenomena of these systems at normal gravity. Microgravity tests in the NASA Glenn 2.2 second drop tower were performed (1) to demonstrate the feasibility of performing propellant experiments using the NASA Glenn microgravity facilities, (2) to develop the operational procedures for safe handing of the energetic materials and disposal of their toxic combustion by-products and (3) to obtain initial measurements of the AP burning rate and flame structure under microgravity conditions. Experiments were conducted on the CH4/AP system previously studied at normal gravity using a modified design of the counterflow burner and a NASA Glenn Pig Rig, i.e., one of the existing drop rigs for general-purpose usage. In these experiments, the AP burning rate was measured directly with a linear variable differential transducer (LVDT) and video imaging of the flame structure was recorded ignition was achieved by hot wires stretched across the AP surfaces. Initial drop tower combustion data show that with the same burner separation distance and flow conditions of the normal gravity experiments, the AP burning rate is approximately a factor of two lower. This difference is likely a result of radiation effects, but further tests with longer test times need to be conducted to verify that steady state conditions were achieved under microgravity conditions.

Takahashi, Fumiaki↗
DOE OSTI2025

Autonomous direct freeform fabrication strategy for multi-axis additive manufacturing

Multi-axis additive manufacturing (M-AM) enables precise material deposition along both planar and curved layers, eliminating the need for support structures through a continuous material deposition approach. In contrast to conventional 2-dimensional planar layers constrained to a fixed building orientation, the deposition on freeform layers demands the specification of guided curves to determine material deposition directions which are no longer to be fixed to a build direction. There are challenges that arise when fabricating components with multiple “build” directions, necessitating the decomposition of geometries and the specification of guided curves for the resulting volumes. Furthermore, multi-axis systems introduce heightened challenges due to an increased degree of freedom in motion. Consequently, the potential risks of collision between the deposited geometry and the motion platform become a notable concern. This research proposes a freeform layering algorithm to address the challenge of seamless transitions between planar and curved layers in the process planning of M-AM. The algorithm computes 3D “printable” layers by leveraging topological information derived from the geometry to be built and integrates collision-free manufacturability considerations into the computational process. These accumulated volumes serve as a “substrate” and support volumes for subsequent deposition, allowing later layers to be built without the need for additional support material. In conclusion, the proposed method successfully devises a freeform layering approach suitable for intricate models that demand substantial support, thus enabling the fabrication of diverse geometries in a manner previously unachievable.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Surface Chemistry of Methanol on Cu 3 Pd(111): Effects of Metal Alloying and Reaction with Hydrogen

Synchrotron-based ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) was used to study the adsorption and surface chemistry of methanol on a Cu 3 Pd(111) model surface. The composition and morphological properties of the pristine Cu 3 Pd(111) substrate were analyzed using a combination of low-energy electron diffraction (LEED), scanning tunneling microscopy (STM), and low-energy ion scattering (LEIS). The results of ion scattering showed segregation of Pd toward the surface, with a Pd/Cu ratio close to 0.5, a larger value than the ratio of 0.33 expected for a Cu 3 Pd bimetallic structure. The surface of the alloy exhibited a good LEED pattern with three-fold long-range periodicities. In STM, clusters of palladium with hexagonal arrays and Pd- Pd distances of 2.7-2.8 Å were detected. Bonding to copper perturbed the electronic properties of the atoms in the Pd clusters, shifting their 4d states toward higher binding energy with respect to the Fermi level. Further, the valence band spectrum of Cu 3 Pd(111) exhibited a line shape that was very different from those displayed by Cu(111) or Pd(111). At low pressures, the adsorption of methanol on Cu 3 Pd(111) at 300 K mainly produced CH 3 O, CO and CH x species. AP-XPS showed that most Pd atoms in the surface of the Cu 3 Pd(111) alloy interacted with the decomposition products of methanol. No significant changes were observed in the core levels of copper upon the adsorption and dissociation of methanol, suggesting that the molecule mainly interacted with Pd sites of the alloy. Reaction with hydrogen led to fast removal of CH x , C and PdC x species from Cu 3 Pd(111) at moderate (< 450 K) temperatures and prevented a CH x → C transformation. If the stability of adsorbed CH 3 O is used as a descriptor for the hydrogenation of CO 2 to methanol, Cu 3 Pd should be a much better catalyst than monometallic palladium. This may be a consequence of electronic and ensemble effects in the alloy that moderate the reactivity of Pd sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Leveraging High-resolution Molecular Composition of Soil Organic Matter to Enhance Carbon Cycling Modeling

Soils store more carbon than the atmosphere and vegetation combined, yet Earth system models still struggle to predict how this vast reservoir will respond to environmental change. A central limitation is that most soil biogeochemical models represent organic matter using bulk conceptual pools or chemically homogeneous fractions, preventing direct use of rapidly expanding molecular-scale datasets. Here we develop and test a new soil decomposition framework that explicitly integrates high-resolution information on organic matter composition. First, we construct a molecularly informed litter decomposition module in which plant inputs are partitioned into five functional compound classes—carbohydrates, proteins, lignin-like aromatics, lipids, and carbonyls—using a molecular mixing model calibrated to solid-state 13 C Nuclear Magnetic Resonance (NMR) spectra. Class-specific kinetics, lignin-dependent physical protection, and substrate-driven microbial carbon use efficiency allow the module to capture metabolic tradeoffs associated with enzyme production and nutrient limitation. We then embed this litter module within a microbially explicit whole-soil model that tracks the transformation of these compound classes through particulate organic matter, dissolved organic matter, mineral-associated organic matter, and microbial biomass. High-resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry (FTICR-MS) data are used to link internal pools to measurable soil organic matter fractions and to constrain key process parameters. Applications at soil-core and ecosystem scales demonstrate that the new model reproduces observed soil respiration dynamics while providing mechanistic attribution of CO 2 fluxes to specific chemical classes and pools. Compared to existing frameworks such as the Community Land Model soil biogeochemistry module and the Millennial model, our approach maintains competitive predictive skill while substantially improving interpretability and opportunities for data–model integration. This work illustrates a viable pathway for leveraging molecular-scale observations to reduce structural uncertainty in soil carbon–climate feedback projections.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Second Generation RLV Space Vehicle Concept

NASA has a long history of conducting development programs and projects in a consistent fashion. Systems Engineering within those programs and projects has also followed a given method outlined by such documents as the NASA Systems Engineering Handbook. The relatively new NASA Space Launch Initiative (SLI) is taking a new approach to developing a space vehicle, with innovative management methods as well as new Systems Engineering processes. With the program less than a year into its life cycle, the efficacy of these new processes has yet to be proven or disproven. At $776M for phase 1, SLI represents a major portion of the NASA focus; however, the new processes being incorporated are not reflected in the training provided by NASA to its engineers. The NASA Academy of Program and Project Leadership (APPL) offers core classes in program and project management and systems engineering to NASA employees with the purpose of creating a "knowledge community where ideas, skills, and experiences are exchanged to increase each other's capacity for strong leadership". The SLI program is, in one sense, a combination of a conceptual design program and a technology program. The program as a whole doesn't map into the generic systems engineering project cycle as currently, and for some time, taught. For example, the NASA APPL Systems Engineering training course teaches that the "first step in developing an architecture is to define the external boundaries of the system", which will require definition of the interfaces with other systems and the next step will be to "define all the components that make up the next lower level of the system hierarchy" where fundamental requirements are allocated to each component. Whereas, the SLI technology risk reduction approach develops architecture subsystem technologies prior to developing architectures. The higher level architecture requirements are not allowed to fully develop and undergo decomposition and allocation down to the subsystems before the subsystems must develop allocated requirements based on the highest level of requirements. In the vernacular of the project cycles prior to the mid 1990's, the architecture definition portion of the program appears to be at a generic Phase A stage, while the subsystems are operating at Phase B. Even the management structure of the SLI program is innovative in its approach to Systems Engineering and is not reflected in the APPL training modules. The SLI program has established a Systems Engineering office as an office separate from the architecture development or the subsystem technology development, while that office does have representatives within these other offices. The distributed resources of the Systems Engineering Office are co-located with the respective Project Offices. This template is intended to provide systems engineering as an integrated function at the Program Level. the program management of SLI and the MAT agree that "program/project managers and the systems engineering team must work closely together towards the single objective of delivering quality products that meet the customer needs". This paper will explore the differences between the methods being taught by NASA, which represent decades of ideas, and those currently in practice in SLI. Time will tell if the innovation employed by SLI will prove to be the model of the future. For now, it is suggested that the training of the present exercise the flexibility of recognizing the new processes employed by a major new NASA program.

Bailey, Michelle↗
DOE OSTI2026

The evolution of coal porosity during pyrolysis

Gasification of coal, municipal waste, or other organic materials is a potential hydrogen source that entails complex thermal decomposition and transport processes. This study provides a multiscale analysis of these processes for sub-bituminous (Usibelli, Healy, Alaska) and lignite (Center, North Dakota) coals and provides data useful for process design. The chemistry, mineralogy, and pore structures of pyrolyzed coal and their evolution with thermal decomposition are discussed. Samples pyrolyzed at 200–1000 °C were analyzed by small-angle neutron scattering; ultra-small, small-, and wide-angle X-ray scattering; and other complementary techniques. Scanning electron microscopy showed new pores in the high-temperature-pyrolyzed material. Upon heating, the coals became progressively denser, and the concentration of hydrogen decreased. Changes in pore volume fell into three temperature ranges: an initial, low-temperature range that, for the Usibelli coal, involved an increase in overall porosity; a mid-temperature range associated with pore volume loss; and a high-temperature range associated with significant porosity increase and char formation. This transformation was paralleled by changes in fractal dimension and correlation length. The higher the pyrolysis temperature the greater the small-pore-volume fraction and overall surface area became. Pyrolysis increased the lateral size of coal crystallites, decreased the amorphous fraction, and increased the aromatics fraction and overall coal rank. Comparisons of neutron and X-ray scattering data and subsequent water uptake studies showed that pre-dried coals can re-hydrate relatively rapidly upon exposure to air, which can significantly affect the porosity calculated from small-angle-scattering data. Fits to the cumulative porosity curves provide a method for modeling the physical and chemical transformation of hydrogen-containing feedstock during gasification.

Anovitz, Lawrence {Larry} [ORNL] (ORCID:0000000226↗
NASA NTRS2024

Exploration Systems Development Mission Directorate: Moon to Mars Architecture Definition Document

The National Aeronautics and Space Administration (NASA) explores the unknown in air and space, innovates for the benefit of humanity, and inspires the world through discovery. Extending the reach of humanity through the human exploration of the Moon, Mars, and beyond is key to that mission. NASA’s Moon to Mars Strategy and Objectives document establishes long-term goals and objectives for crewed deep space exploration; however, satisfying NASA’s Moon to Mars Objectives requires an innovative approach to the definition, management, and execution of NASA’s Moon to Mars Architecture. An architecture offers a high-level unifying structure and defines a system. It provides rules, guidelines, and constraints that define a cohesive and coherent framework that identifies constituent parts, relationships, and connections and establishes how those parts fit and work together. This Architecture Definition Document (ADD) establishes the process for the decomposition of objectives empowers the agency’s success in achieving human exploration of the cosmos. NASA updates this document annually to reflect the maturation of the architecture and the progress NASA and partners make toward achieving exploration objectives. The ADD is not a manifest or requirements document. Instead, it serves as a tool for the programs, projects, and engineers who will implement and execute NASA’s bold ambitions for crewed exploration of deep space. As established in the Moon to Mars Strategy and Objectives, “Why” we explore encompasses three pillars: Science, Inspiration, and National Posture. Ensuring success in all three areas requires an architectural approach that incorporates innovation, collaboration, and partnerships that can be sustained across a multi-decadal effort. This second revision (Rev-B) of the ADD, developed to support NASA’s 2024 Architecture Concept Review (ACR), incorporates several key updates to support the continued evolution of the architecture. Since the last revision of the ADD, NASA has significantly improved the clarity of the objective decomposition, which distills exploration objectives into the characteristics and needs and use cases and functions needed to achieve them. The updated decomposition incorporates findings from internal studies and diverse stakeholder feedback. A model-based systems engineering approach ensures coherence and consistency, removing inconsistency and repetition. Revision B also incorporates advancements to NASA’s Mars architecture, including insight into initial capabilities, systems, and operations necessary to support the Humans to Mars segment. Updates to objective decomposition for Mars add significant detail to the ADD and hint at areas of forward work and future study. An appendix adds greater depth in the future decisions needed for Mars that will drive lunar needs. They are not the only decisions to be made, but they will have huge effects on subsequent decisions. NASA continues to introduce new exploration systems into the architecture. Two new elements — initial surface habitat and lunar surface cargo lander—successfully passed mission concept review in 2024 as a result of extensive analysis, concept refinement, and studies. These elements and their respective reference missions appear in this revision. NASA also continues to apply architecture processes to cross-agency efforts and coordination with external stakeholders by including definitions of architecture technology gaps — essential areas for engagement across and beyond the agency. The technology gaps appendix identifies areas that need attention and innovation to enable future exploration. In publishing this information, NASA communicates the technologies and capabilities that may benefit from partnership with industry, academia, other U.S. government agencies, and international space agencies. Ultimately, NASA established the Moon to Mars Architecture approach to communicate and facilitate humanity’s journey into the universe according to the principles and recurring tenets of NASA’s Moon to Mars Strategy and Objectives. The NASA architecture team thanks their many stakeholders, participants, and partners for their efforts to review and provide feedback. Their support has been critical to the success of this approach.

Elements↗
DOE OSTI2026

Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations

We develop new approximate compilation schemes that significantly reduce the expense of compiling the Quantum Approximate Optimization Algorithm (QAOA) for solving the Max-Cut problem. Our main focus is on compilation with trapped-ion simulators using Pauli-X operations and all-to-all Ising Hamiltonian HIsing evolution generated by Molmer-Sorensen or optical dipole force interactions, though some of our results also apply to standard gate-based compilations. Our results are based on principles of graph sparsification and decomposition; the former reduces the number of edges in a graph while maintaining its cut structure, while the latter breaks a weighted graph into a small number of unweighted graphs. Though these techniques have been used as heuristics in various hybrid quantum algorithms, there have been no guarantees on their performance, to the best of our knowledge. This work provides the first provable guarantees using sparsification and decomposition to improve quantum noise resilience and reduce quantum circuit complexity. For quantum hardware that uses edge-by-edge QAOA compilations, sparsification leads to a direct reduction in circuit complexity. For trapped-ion quantum simulators implementing all-to-all HIsing pulses, we show that for a (1−ϵ) factor loss in the Max-Cut approximation (ϵ>0), our compilations improve the (worst-case) number of HIsing pulses from O(n2) to O(nlog(n/ϵ)) and the (worst-case) number of Pauli-X bit flips from O(n2) to O(nlog(n/ϵ)ϵ2) for n-node graphs. This is an asymptotic improvement for any constant ϵ>0. We demonstrate that significant improvements to the approximation ratio are obtained using decomposition in simulated trapped-ion experiments with dephasing noise. We further present a generic argument showing that sparsification results in an exponentially improved circuit fidelity lower bound in digital computing schemes based on one- and two-qubit gates, which are relevant to a wide variety of hardwares such as superconducting qubits and certain neutral atom or trapped ion setups, and more sophisticated noise models. We anticipate these approximate compilation techniques will be useful tools in a variety of future quantum computing experiments.

Moondra, Jai [Georgia Institute of Technology]↗