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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

ReactionMechanismSimulator.jl: A modern approach to chemical kinetic mechanism simulation and analysis

Abstract We present ReactionMechanismSimulator.jl (RMS), a modern differentiable software for the simulation and analysis of chemical kinetic mechanisms, including multiphase systems. RMS has already been applied to problems in combustion, pyrolysis, polymers, pharmaceuticals, catalysis, and electrocatalysis. RMS is written in Julia, making it easy to develop and allowing it to take advantage of Julia's extensive numerical computing ecosystem. In addition to its extensive library of optimized analytic Jacobians, RMS can generate and use Jacobians computed using automatic differentiation and symbolically generated analytic Jacobians. RMS is demonstrated to be faster than Cantera and Chemkin in several benchmarks. RMS also implements an extensive set of features for analyzing chemical mechanisms, including a library of easy‐to‐call plotting functions, molecular structure resolved flux diagram generation, crash analysis, traditional sensitivity analysis, transitory sensitivity analysis, and an automatic mechanism analysis toolkit. RMS implements efficient adjoint and parallel forward sensitivity analyses. We also demonstrate the ease of adding new features to RMS.

Johnson, Matthew S.↗
DOE OSTI2020

Application of radiochromic gel dosimetry to commissioning of a megavoltage research linear accelerator for small–field animal irradiation studies

To develop and implement an efficient and accurate commissioning procedure for small-field static beam animal irradiation studies on an MV research linear accelerator (Linatron-M9) using radiochromic gel dosimetry. The research linear accelerator (Linatron-M9) is a 9 MV linac with a static fixed collimator opening of 5.08 cm diameter. Lead collimators were manually placed to create smaller fields of 2 × 2 cm 2 , 1 × 1 cm 2 , and 0.5 × 0.5 cm 2 . Relative dosimetry measurements were performed, including profiles, percent depth dose (PDD) curves, beam divergence, and relative output factors using various dosimetry tools, including a small volume ionization chamber (A14), GAFCHROMIC™ EBT3 film, and Clearview gel dosimeters. The gel dosimeter was used to provide a 3D volumetric reference of the irradiated fields. The Linatron profiles and relative output factors were extracted at a reference depth of 2 cm with the output factor measured relative to the 2 × 2 cm 2 reference field. Absolute dosimetry was performed using A14 ionization chamber measurements, which were verified using a national standards laboratory remote dosimetry service. Absolute dosimetry measurements were confirmed within 1.4% (k = 2, 95% confidence = 5%). The relative output factor of the small fields measured with films and gels agreed with a maximum relative percent error difference between the two methods of 1.1 % for the 1 × 1 cm 2 field and 4.3 % for the 0.5 × 0.5 cm 2 field. These relative errors were primarily due to the variability in the collimator positioning. The measured beam profiles demonstrated excellent agreement for beam size (measured as FWHM), within approximately 0.8 mm (or less). Film measurements were more accurate in the penumbra region due to the film’s finer resolution compared with the gel dosimeter. Following the van Dyk criteria, the PDD values of the film and gel measurements agree within 11% in the buildup region starting from 0.5 cm depth and within 2.6 % beyond maximum dose and into the fall-off region for depths up to 5 cm. The 2D beam profile isodose lines agree within 0.5 mm in all regions for the 0.5 × 0.5 cm 2 and the 1 × 1 cm 2 fields and within 1 mm for the larger field of 2 × 2 cm 2 . The 2D PDD curves agree within approximately 2% of the maximum in the typical therapy region (1–4 cm) for the 1 × 1 cm 2 and 2 × 2 cm 2 and within 5% for the 0.5 × 0.5 cm 2 field. This work provides a commissioning process to measure the beam characteristics of a fixed beam MV accelerator with detailed dosimetric evaluation for its implementation in megavoltage small animal irradiation studies. Radiochromic gel dosimeters are efficient small-field relative dosimetry tools providing 3D dose measurements allowing for full representation of dose, dosimeter misalignment corrections and high reproducibility with low inter-dosimeter variability. Altogether, radiochromic gels are valuable for fast, full relative dosimetry commissioning in comparison to films for application in high-energy small-field animal irradiation studies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Algebraic multigrid preconditioning of the Hessian in optimization constrained by a partial differential equation

Summary We construct an algebraic multigrid (AMG) based preconditioner for the reduced Hessian of a linear‐quadratic optimization problem constrained by an elliptic partial differential equation. While the preconditioner generalizes a geometric multigrid preconditioner introduced in earlier works, its construction relies entirely on a standard AMG infrastructure built for solving the forward elliptic equation, thus allowing for it to be implemented using a variety of AMG methods and standard packages. Our analysis establishes a clear connection between the quality of the preconditioner and the AMG method used. The proposed strategy has a broad and robust applicability to problems with unstructured grids, complex geometry, and varying coefficients. The method is implemented using the Hypre package and several numerical examples are presented.

Barker, Andrew T.↗
DOE OSTI2020

A matrix-free approach for finite-strain hyperelastic problems using geometric multigrid

This paper investigates matrix-free algorithms for problems in quasi-static finite-strain hyperelasticity. Iterative solvers with matrix-free operator evaluation have emerged as an attractive alternative to sparse matrices in the fluid dynamics and wave propagation communities because they significantly reduce the memory traffic, the limiting factor in classical finite element solvers. Specifically, we study different matrix-free realizations of the finite element tangent operator and determine whether generalized methods of incorporating complex constitutive behavior might be feasible. Furthermore, in order to improve the convergence behavior of iterative solvers, we also propose a method by which to construct level tangent operators and employ them to define a geometric multigrid preconditioner. Additionally, the performance of the matrix-free operator and the geometric multigrid preconditioner is compared to the matrix-based implementation with an algebraic multigrid (AMG) preconditioner on a single node for a representative numerical example of a heterogeneous hyperelastic material in two and three dimensions. We find that matrix-free methods for finite-strain solid mechanics are very promising, outperforming linear matrix-based schemes by two to five times, and that it is possible to develop numerically efficient implementations that are independent of the hyperelastic constitutive law.

42 ENGINEERING↗
DOE OSTI2022

The strip method for shape derivatives

Abstract A major challenge in shape optimization is the coupling of finite element method (FEM) codes in a way that facilitates efficient computation of shape derivatives. This is particularly difficult with multiphysics problems involving legacy codes, where the costs of implementing and maintaining shape derivative capabilities are prohibitive. The volume and boundary methods are two approaches to computing shape derivatives. Each has a major drawback: the boundary method is less accurate, while the volume method is more invasive to the FEM code. We introduce the strip method , which computes shape derivatives on a strip adjacent to the boundary. The strip method makes code coupling simple. Like the boundary method, it queries the state and adjoint solutions at quadrature nodes, but requires no knowledge of the FEM code implementations. At the same time, it exhibits the higher accuracy of the volume method. As an added benefit, its computational complexity is comparable to that of the boundary method, that is, it is faster than the volume method. We illustrate the benefits of the strip method with numerical examples.

Hardesty, Sean↗
DOE OSTI2023

Dirichlet-type absorbing boundary conditions for peridynamic scalar waves in two-dimensional viscous media

Construction of absorbing boundary conditions (ABCs) for nonlocal models is generally challenging, primarily due to the fact that nonlocal operators are commonly associated with volume constrained boundary conditions. Moreover, application of Fourier and Laplace transforms, which are essential for the majority of available methods for ABCs, to nonlocal models is complicated. In this paper, we propose a simple method to construct accurate ABCs for peridynamic scalar wave-type problems in viscous media. The proposed ABCs are constructed in the time and space domains and are of Dirichlet type. Consequently, their implementation is relatively simple, since no derivatives of the wave field are required. The proposed ABCs are derived at the continuum level, from a semi-analytical solution of the exterior domain using harmonic exponential basis functions in space and time (plane-wave modes). The numerical implementation is done using a meshfree collocation approach employed within a boundary layer adjacent to the interior domain boundary. The modes satisfy the peridynamic numerical dispersion relation, resulting in a compatible solution of the interior region (near-field) with that of the exterior region (far-field). The accuracy and stability of the proposed ABCs are demonstrated with several numerical examples in two-dimensional unbounded domains.

42 ENGINEERING↗
DOE OSTI2023

A robust interface finite element formulation for modeling brittle material failure problems

Abstract Failure of many brittle materials and structures can be modeled using interface‐oriented finite elements combined with intrinsic cohesive zone models. The discontinuous Galerkin (DG) finite element method provides an innovative framework for modeling brittle crack propagation with zero‐thickness interface elements, which can accommodate extrinsic cohesive laws to avoid the artificial compliance required in intrinsic cohesive models. However, robust formulations and implementations of DG methods are critical in alleviating the well‐known convergence issues for both crack nucleation and propagation with reduced instability. This paper presents a robust interface element formulation by modifying the incomplete interior penalty Galerkin (IIPG) method, which successfully avoids the initial element interface penetration across elements that occurs prior to crack nucleation, and thereby greatly reduces the instability issue as cracks open. We further verified and validated our implementation by using a bar tension test and a beam fracturing benchmark. The robustness of our proposed interface element method was demonstrated by a micromechanics fiber/matrix debonding problem with 64 fibers embedded in a bulk matrix.

Liu, Ruijie↗
DOE OSTI2021

Efficient quadrature rules for finite element discretizations of nonlocal equations

Here, in this paper, we design efficient quadrature rules for finite element (FE) discretizations of nonlocal diffusion problems with compactly supported kernel functions. Two of the main challenges in nonlocal modeling and simulations are the prohibitive computational cost and the nontrivial implementation of discretization schemes, especially in three-dimensional settings. In this work, we circumvent both challenges by introducing a parametrized mollifying function that improves the regularity of the integrand, utilizing an adaptive integration technique, and exploiting parallelization. We first show that the “mollified” solution converges to the exact one as the mollifying parameter vanishes, then we illustrate the consistency and accuracy of the proposed method on several two- and three-dimensional test cases. Furthermore, we demonstrate the good scaling properties of the parallel implementation of the adaptive algorithm and we compare the proposed method with recently developed techniques for efficient FE assembly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A non‐intrusive domain‐decomposition model reduction method for linear steady‐state partial differential equations with random coefficients

Abstract Domain decomposition methods have been proved to be an effective strategy to reduce the dimension of parametric partial differential equations (PDEs). However, existing domain decomposition methods for parametric PDEs are usually intrusive, which means domain decomposition based solvers need to be implemented from scratch for each target parametric PDE. To address this issue, we develop a new non‐intrusive domain‐decomposition model reduction method for linear steady‐state PDEs with random‐field coefficients. As a variant of our previous work by Mu and Zhang, the new method only needs access to the final linear system, that is, the global stiffness matrix and the right hand side, of a deterministic PDE solver, in order to build a domain‐decomposition‐based reduced model without intrusive implementation from scratch. The key idea is to remove the interface condition between sub‐domains and rely on the correlation between columns of the linear system to couple the sub‐domains. The non‐intrusive feature enables the applicability of the proposed method to a broader class of uncertainty quantification problems, where many legacy codes/solvers can be fully reused by our method. Two numerical examples including diffusion equations with random diffusivity and convection‐dominated transport with random velocity, are provided to demonstrate the effectiveness and efficiency of our method.

Zhang, Guannan↗
DOE OSTI2025

Uncertainty Quantification Enabled by Automatic Differentiation for Hydrodynamic Simulation of Shock‐to‐Detonation Transition in High Explosives

Quantifying the effects of uncertainty in a reactive burn model on the run-to-detonation time in high explosives (HEs) provides a robust methodology for assessing the probability of an HE failing the IHE qualification standard. Moreover, uncertainty quantification helps evaluate whether the model calibration accurately represents data outside the calibration set. This study uses a specialized hydrodynamic simulation code for modeling detonation to determine the run-to-detonation time of the HE PBX 9502 for various impact velocities. To quickly approximate uncertainties in the model, a surrogate was constructed using a Taylor series expansion centered at the mean of the input parameters. To obtain the sensitivities required for constructing the Taylor series, HYP-percomplex Automatic Differentiation (HYPAD) was implemented. HYPAD is a methodology for infusing existing codes with automatic differentiation capabilities by augmenting variables with one or more imaginary units to compute step-size independent partial derivatives. These derivatives are accurate to machine precision with respect to the implemented numerical algorithm, meaning their accuracy reflects that of the underlying method (e.g., integration or discretization schemes). Using reduced order modeling techniques, the mean and standard deviation of the run-to-detonation time of a shock within PBX 9502 were computed for a number of initial impact velocities. A weighted least squares regression was then performed to obtain a best fit curve and prediction interval for the computed statistics. Historical data points from explosively driven wedge tests were utilized to validate the prediction interval, ensuring its reliability in predicting future outcomes. With this prediction interval and a known safety constraint curve, the most probable point of failure and the probability of failure for the HE PBX 9502 were determined.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Changes in wild pig ( Sus scrofa ) relative abundance, crop damage, and environmental impacts in response to control efforts

BACKGROUND: As the population and range of wild pigs (Sus scrofa) continue to grow across North America, there has been an increase in environmental and economic damages caused by this invasive species, and control efforts to reduce damages have increased concomitantly. Despite the expanding impacts and costs associated with population control of wild pigs, the extent to which wild pig control reduces populations and diminishes environmental and agricultural damages are rarely quantified. The goal of this study is to quantify changes in wild pig relative abundance and subsequent changes in damages caused by invasive wild pigs in response to control. RESULTS: Using a combination of wild pig population surveys, agricultural damage assessments, and environmental rooting surveys across 19 mixed forest-agricultural properties in South Carolina, USA, we quantified changes in wild pig relative abundance and associated damages over a 3-year period following implementation of a professional control program. Following implementation of control efforts, both the number of wild pig detections and estimated abundance decreased markedly. Within 24 months relative abundance was reduced by an average of ~70%, which resulted in a corresponding decline in environmental rooting damage by ~99%. CONCLUSION: Our findings suggest that sustained wild pig control efforts can substantially reduce wild pig relative abundance, which in turn resulted in a reduction in environmental rooting damage by wild pigs. Ultimately this study will help fill critical knowledge gaps regarding the efficacy of wild pig control programs and the effort needed to reduce impacts to native ecosystems, livestock, and crops. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A Poisson–Nernst–Planck Model of Ion Transport and Interface Segregation in Metal–Insulator–Semiconductor Structures and Solar Cells

A numerical model that describes the transport of mobile ionic species in metal–insulator–semiconductor (MIS) and photovoltaic (PV) devices subject to temperature and voltage stress is presented. The finite element method (FEM) is used to solve the Nernst–Planck equation while imposing Poisson's equation self-consistently as a restriction for the electrostatic potential. This allows the contribution of the ionic species to the potential to be taken into account. Using a variational formulation eases the implementation of diverse boundary conditions, including the incorporation of segregation kinetics at the device interfaces. Segregation across the dielectric–semiconductor interface is relevant to modeling the electronic device degradation in systems where contamination reaches the semiconductor. The model in closed systems with no-flux boundary conditions is validated first. In the limiting case of low contamination levels with respect to the gate bias, the FEM solution matches analytically derived approximations. Then, the implementation is broadened to include an open boundary at the dielectric–semiconductor interface to account for leakage of ions. The predicted time dependence of the flatband voltage in Na-contaminated MIS test structures agrees well with measurements. This model successfully captures the role of long-range ion transport at concentrations of relevance to electronic and PV device instability and neuromorphic computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

State preparation and evolution in quantum computing: a perspective from Hamiltonian moments

Quantum algorithms on the noisy intermediate-scale quantum (NISQ) devices are expected to simulate quan- tum systems that are classically intractable to demonstrate quantum advantages. However, the non-negligible gate error on the NISQ devices impedes the conventional quantum algorithms to be implemented. Practical strategies usually exploit hybrid quantum-classical quantum algorithms to demonstrate potentially useful ap- plications of quantum computing in the NISQ era. Among the numerous hybrid quantum-classical algorithms, recent efforts highlight the development of quantum algorithms based upon quantum computed Hamiltonian moments, ?f|Hˆn|f? (n = 1, 2, · · · ), with respect to quantum state |f?. In this tutorial, we will give a brief review of these quantum algorithms with focuses on the typical ways of computing Hamiltonian moments using quantum hardware and improving the accuracy of the estimated state energies based on the quantum computed moments. Furthermore, we will present a tutorial to show how we can measure and compute the Hamiltonian moments of a four-site Heisenberg model, and compute the energy and magnetization of the model utilizing the imaginary time evolution in the real IBM-Q NISQ hardware environment. Along this line, we will further discuss some practical issues associated with these algorithms. We will conclude this tutorial review by overviewing some possible developments and applications in this direction in the near future.

Aulicino, Joseph C.↗
DOE OSTI2023

Pairwise‐Parallel Entangling Gates on Orthogonal Modes in a Trapped‐Ion Chain

Abstract Parallel operations are important for both near‐term quantum computers and larger‐scale fault‐tolerant machines because they reduce execution time and qubit idling. This study proposes and implements a pairwise‐parallel gate scheme on a trapped‐ion quantum computer. The gates are driven simultaneously on different sets of orthogonal motional modes of a trapped‐ion chain. This work demonstrates the utility of this scheme by creating a Greenberger‐Horne‐Zeilinger (GHZ) state in one step using parallel gates with one overlapping qubit. It also shows its advantage for circuits by implementing a digital quantum simulation of the dynamics of an interacting spin system, the transverse‐field Ising model. This method effectively extends the available gate depth by up to two times with no overhead when no overlapping qubit is involved, apart from additional initial cooling. This scheme can be easily applied to different trapped‐ion qubits and gate schemes, broadly enhancing the capabilities of trapped‐ion quantum computers.

Optics↗
DOE OSTI2026

A Review of Software for Designing and Operating Quantum Networks

Quantum networks development is crucial to realizing a production-grade network that can support distributed sensing, secure communication, and utility-scale quantum computation. However, the transition from laboratory demonstration to deployable networks requires software implementations of architectures and protocols tailored to the unique constraints of quantum systems. This paper reviews the current state of software implementations for quantum networks, organized around a three-plane abstraction of infrastructure, logical, and control/service planes. We cover software for both designing quantum network protocols (e.g., SeQUeNCe, QuISP, and NetSquid) and operating testbeds, with a focus on essential control/service plane functions such as entanglement, topology, and resource management, in a proposed taxonomy. Our review highlights a persistent gap between theoretical architecture and protocol proposals and their realization in simulators or testbeds, particularly in dynamic topology and network management. We conclude by outlining open challenges and proposing a roadmap for developing scalable software architectures to enable hybrid, large-scale quantum networks.

Network Design↗
DOE OSTI2024

The ReSWARM microgravity flight experiments: Planning, control, and model estimation for on‐orbit close proximity operations

Abstract On‐orbit close proximity operations involve robotic spacecraft maneuvering and making decisions for a growing number of mission scenarios demanding autonomy, including on‐orbit assembly, repair, and astronaut assistance. Of these scenarios, on‐orbit assembly is an enabling technology that will allow large space structures to be built in situ, using smaller building block modules. However, like many of these scenarios, robotic on‐orbit assembly involves several technical hurdles, such as changing system models. For instance, grappled modules moved by a free‐flying “assembler” robot can cause significant changes in the combined system inertia, which have cascading impacts on motion planning and control portions of the autonomy stack. Further, on‐orbit assembly and other scenarios require collision‐avoiding motion planning, particularly when operating in a “construction site” scenario of multiple assembler robots and structures. Multiple key technologies that address these complicating factors for autonomous microgravity close proximity operations are detailed in this work, in particular: (1) application of global long‐horizon planning, accomplished using offline and online sampling‐based planner options that consider the system dynamics; (2) adaptation of the recently proposed RATTLE information‐aware planning framework for on‐orbit reconfiguration model learning; and (3) connection with robust control tools to provide low‐level control robustness using current system knowledge. These approaches were demonstrated for an autonomous on‐orbit assembly use case by the RElative Satellite sWarming and Robotic Maneuvering (ReSWARM) experiments using NASA's Astrobee robots on the International Space Station. Results of the ReSWARM experiments are provided along with significant operational and implementation detail discussing the practicalities of hardware implementation and unique aspects of working with the Astrobee free‐flyer robots in microgravity. ReSWARM provides a base set of planning and control tools for robotic close proximity operations, demonstrates them in microgravity, and outlines some of the important hardware aspects that future autonomous free‐flyers will need to consider.

Robotics↗
DOE OSTI2020

Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition

Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.

Hanson, Joshua↗

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