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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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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Performance of a Robotic Assistance Device in Computed Tomography-Guided Percutaneous Diagnostic and Therapeutic Procedures

PurposeTo evaluate a commercially available robotic assistance device for computed tomography-guided diagnostic and therapeutic interventions, compared to regular, manually performed CT scan-guided interventions in terms of precision, exposure to radiation to the patient and intervention time.Materials and MethodsOver a period of 6 months, 55 consecutive patients were recruited and treated using robotic assistance and compared to a control group of 101 patients previously treated with a regular CT scan-guided, manual approach. Evaluated parameters were precision (deviation from planned target and number of needle replacements), radiation exposure to the patient and intervention time. Evaluations were performed with regard to complexity (in-plane vs out-of-plane interventions) and type of anesthesia (general vs local).ResultsParameters related to precision were in general significantly better in the robotic assistance group (p < 0.01) with a mean deviation of 1.2 mm (± 1.6 mm) compared to 2.6 mm (± 1.1 mm) in the comparison group. Compared to manual procedure, the mean intervention time was reduced by 15 min (± 5.4 min) on average for an out-of-plane needle placement in the robotic group. There was no increase of exposure to radiation to the patient while radiation exposure for the physician was reduced to zero when the navigation system was used.ConclusionCompared to manual placement, the use of a robotic assistance device in out-of-plane CT-guided interventions under general anesthesia allows for probe placement with high precision. Intervention time is reduced with no increase of exposure to radiation to the patient.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

PDE-constrained high-order mesh optimization

Here, we present a novel framework for PDE-constrained r-adaptivity of high-order meshes. The proposed method formulates mesh movement as an optimization problem, with an objective function defined as a convex combination of a mesh quality metric and a measure of the accuracy of the PDE solution obtained via finite element discretization. The proposed formulation achieves optimized, well-defined high-order meshes by integrating mesh quality control, PDE solution accuracy, and robust gradient regularization. We adopt the Target-Matrix Optimization Paradigm to control geometric properties across the mesh, independent of the PDE of interest. To incorporate the accuracy of the PDE solution, we introduce error measures that control the finite element discretization error. The implicit dependence of these error measures on the mesh nodal positions is accurately captured by adjoint sensitivity analysis. Additionally, a convolution-based gradient regularization strategy is used to ensure stable and effective adaptation of high-order meshes. We demonstrate that the proposed framework can improve mesh quality and reduce the error by up to 10 times for the solution of Poisson and linear elasto-static problems. The approach is general with respect to the dimensionality, the order of the mesh, the types of mesh elements, and can be applied to any PDE that admits well-defined adjoint operators.

Computer science↗
DOE OSTI2021

A variational phase-field model For ductile fracture with coalescence dissipation

A novel phase-field model for ductile fracture is presented. The model is developed within a consistent variational framework in the context of finite-deformation kinematics. A novel coalescence dissipation introduces a new coupling mechanism between plasticity and fracture by degrading the fracture toughness as the equivalent plastic strain increases. The proposed model is compared with a recent alternative where plasticity and fracture are strongly coupled. Several representative numerical examples motivate specific modeling choices. In particular, a linear crack geometric function provides an “unperturbed” ductile response prior to crack initiation, and Lorentz-type degradation functions ensure that the critical fracture strength remains independent of the phase-field regularization length. In addition, the response of the model is demonstrated to converge with a vanishing phase-field regularization length. Additionally, the model is then applied to calibrate and simulate a three-point bending experiment of an aluminum alloy specimen with a complex geometry. The effect of the proposed coalescence dissipation coupling on simulations of the experiment is first investigated in a two-dimensional plane strain setting. The calibrated model is then applied to a three-dimensional calculation, where the calculated load-deflection curves and the crack trajectory show excellent agreement with experimental observations. Finally, the model is applied to simulate crack nucleation and growth in a specimen from a recent Sandia Fracture Challenge.

42 ENGINEERING↗
DOE OSTI2012

Scalar-particle self-energy amplitudes and confinement in Minkowski space

We analyze the analytic structure of the Covariant Spectator Theory (CST) contribution to the self-energy amplitude for a scalar particle in a {phi}{sup 2}{chi} theory. To this end we derive dispersion relations in 1+1 and in 3+1 dimensional Minkowski space. The divergent loop integrals in 3+1 dimensions are regularized using dimensional regularization. We find that the CST dispersion relations exhibit, in addition to the usual right-hand branch cut, also a left-hand cut. The origin of this "spectator" left-hand cut can be understood in the context of scattering for a scalar {phi}{sup 2}{chi}{sup 2}-type theory. If the interaction kernel contains a linear confining component, its contribution to the self-energy vanishes exactly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Adversarial classification via distributional robustness with Wasserstein ambiguity

Abstract We study a model for adversarial classification based on distributionally robust chance constraints. We show that under Wasserstein ambiguity, the model aims to minimize the conditional value-at-risk of the distance to misclassification, and we explore links to adversarial classification models proposed earlier and to maximum-margin classifiers. We also provide a reformulation of the distributionally robust model for linear classification, and show it is equivalent to minimizing a regularized ramp loss objective. Numerical experiments show that, despite the nonconvexity of this formulation, standard descent methods appear to converge to the global minimizer for this problem. Inspired by this observation, we show that, for a certain class of distributions, the only stationary point of the regularized ramp loss minimization problem is the global minimizer.

Ho-Nguyen, Nam (ORCID:0000000344647730)↗
DOE OSTI2013

Multi-fault Tolerance for Cartesian Data Distributions

Faults are expected to play an increasingly important role in how algorithms and applications are designed to run on future extreme-scale sys- tems. Algorithm-based fault tolerance (ABFT) is a promising approach that involves modications to the algorithm to recover from faults with lower over- heads than replicated storage and a signicant reduction in lost work compared to checkpoint-restart techniques. Fault-tolerant linear algebra (FTLA) algo- rithms employ additional processors that store parities along the dimensions of a matrix to tolerate multiple, simultaneous faults. Existing approaches as- sume regular data distributions (blocked or block-cyclic) with the failures of each data block being independent. To match the characteristics of failures on parallel computers, we extend these approaches to mapping parity blocks in several important ways. First, we handle parity computation for generalized Cartesian data distributions with each processor holding arbitrary subsets of blocks in a Cartesian-distributed array. Second, techniques to handle corre- lated failures, i.e., multiple processors that can be expected to fail together, are presented. Third, we handle the colocation of parity blocks with the data blocks and do not require them to be on additional processors. Several al- ternative approaches, based on graph matching, are presented that attempt to balance the memory overhead on processors while guaranteeing the same fault tolerance properties as existing approaches that assume independent fail- ures on regular blocked data distributions. The evaluation of these algorithms demonstrates that the additional desirable properties are provided by the pro- posed approach with minimal overhead.

Ali, Nawab↗
DOE OSTI2025

Bulk nanocrystalline Al–Mg–Y alloys with amorphous grain boundary complexions display high strength and compressive plasticity

Although nanocrystalline alloys regularly exhibit high strengths, their use in structural applications often face challenges due to sample size limitations, unstable microstructures, and the limited ability to plastically deform. The incorporation of amorphous grain boundary complexions has been proposed to address these issues, by simultaneously stabilizing nanocrystalline grain structures for scale-up processing and improving alloy toughness. In the present study, the mechanical behavior of bulk nanocrystalline Al–Mg–Y is examined with macroscale compression testing, probing a length scale that is relevant to real-world structural applications. Bulk samples were fabricated via a simple powder metallurgy approach, with different hot-pressing temperatures and durations employed for consolidation in order to investigate microstructural and property evolution. All of the specimens contained primary face-centered cubic Al and secondary Al 4 C 3 and Al 3 Y phases, with the Al 3 Y particles exhibiting two populations of small equiaxed and larger elongated particles. Appreciable plasticity was measured along with high ultimate stresses over 800 MPa due to the presence of amorphous grain boundary complexions. Microstructural characterization of fracture surfaces revealed that the area fraction of dimpled regions increased with longer hot-pressing time. Most importantly, the elongated Al 3 Y particles formed regular cellular patterns with increasing hot-pressing time, delaying shear localization and significantly enhancing plasticity. The hierarchy present in the microstructure of the Al–Mg–Y alloy, from amorphous grain boundary complexions to secondary phases, gives rise to excellent bulk mechanical properties, which are attractive for structural applications.

Bulk nanocrystalline alloy↗
DOE OSTI2024

A $C^1$-Conforming Arbitrary-Order Two-Dimensional Virtual Element Method for the Fourth-Order Phase-Field Equation

We present a two-dimensional conforming virtual element method for the fourth-order phase-field equation. Our proposed numerical approach to the solution of this high-order phase-field (HOPF) equation relies on the design of an arbitrary-order accurate, virtual element space with $C^1$ global regularity. Such regularity is guaranteed by taking the values of the virtual element functions and their full gradient at the mesh vertices as degrees of freedom. Attaining high-order accuracy requires also edge polynomial moments of the trace of the virtual element functions and their normal derivatives. In this work, we detail the scheme construction, and prove its convergence by deriving error estimates in different norms. A set of representative test cases allows us to assess the behavior of the method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Clustering and Cliques in Preferential Attachment Random Graphs with Edge Insertion

In this paper, we investigate the global clustering coefficient (a.k.a transitivity) and clique number of graphs generated by a preferential attachment random graph model with an additional feature of allowing edge connections between existing vertices. Specifically, at each time step t, either a new vertex is added with probability f(t), or an edge is added between two existing vertices with probability 1 – f(t). We establish concentration inequalities for the global clustering and clique number of the resulting graphs under the assumption that f(t) is a regularly varying function at infinity with index of regular variation –$\gamma$, where $\gamma$ $\in$ [0, 1). Finally, we also demonstrate an inverse relation between these two statistics: the clique number is essentially the reciprocal of the global clustering coefficient.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Singularly Perturbed System of Parabolic Equations in the Critical Case

We examine a system of singularly perturbed parabolic equations in the case where the small parameter is involved as a coefficient of both time and spatial derivatives and the spectrum of the limit operator has a multiple zero point. In such problems, corner boundary layers appear, which can be described by products of exponential and parabolic boundary-layer functions. Under the assumption that the limit operator is a simple-structure operator, we construct a regularized asymptotics of a solution, which, in addition to corner boundary-layer functions, contains exponential and parabolic boudary-layer functions. The construction of the asymptotics is based on the regularization method for singularly perturbed problems developed by S. A. Lomov and adapted to singularly perturbed parabolic equations with two viscous boundaries by A. S. Omuraliev.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Asymptotics of Traces of Paths in the Young and Schur Graphs

Let G be a graded graph with levels V{sub 0}, V{sub 1}, . . .. Fix m and choose a vertex v in Vn where n ≥ m. Consider the uniform measure on the paths from V{sub 0} to v. Each such path has a unique vertex at the level V{sub m}, so a measure ν{sub v}{sup m} on V{sub m} is induced. It is natural to expect that these measures have a limit as the vertex v goes to infinity in some “regular” way. We prove this (and compute the limit) for the Young and Schur graphs, for which regularity is understood as follows: the fraction of boxes contained in the first row and the first column goes to 0. For the Young graph, this was essentially proved by Vershik and Kerov in 1981; our proof is more straightforward and elementary.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Memory-efficient nonsmooth dynamic optimization using adaptive randomized compression

Dynamic optimization problems arise in many applications including flow control, full waveform inversion, and medical imaging. These problems are plagued by significant computational challenges. One such challenge — and the focus of this work — is the memory limitation induced by the size of the underlying dynamical system. In particular, the entire dynamic trajectory is required for derivative computation and therefore must be stored or recomputed using, e.g., checkpointing. Although recent work demonstrated the use of adaptive randomized sketching to overcome the memory challenge, that work only applies to smooth unconstrained problems, prohibiting its use for nonsmooth regularized and constrained problems. The inclusion of nonsmooth regularizers and constraints is critical as they often arise in an attempt to preserve certain physical properties or to promote sparsity. To solve these problems, we introduce a trust-region algorithm for minimizing the sum of a smooth nonconvex function and a nonsmooth convex function that leverages randomized sketching to compress the dynamical system trajectories and adaptively adjust the sketch rank to satisfy a gradient inexactness condition. We prove convergence of this algorithm and demonstrate that it achieves substantial memory reduction on three discretized PDE-constrained optimization applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Graph decomposition techniques for solving combinatorial optimization problems with variational quantum algorithms

The quantum approximate optimization algorithm (QAOA) has the potential to approximately solve complex combinatorial optimization problems in polynomial time. However, current noisy quantum devices cannot solve large problems due to hardware constraints. In this work, we develop an algorithm that decomposes the QAOA input problem graph into a smaller problem and solves MaxCut using QAOA on the reduced graph. The algorithm requires a subroutine that can be classical or quantum—in this work, we implement the algorithm twice on each graph. One implementation uses the classical solver Gurobi in the subroutine and the other uses QAOA. We solve these reduced problems with QAOA. On average, the reduced problems require only approximately 1/10 of the number of vertices than the original MaxCut instances. Furthermore, the average approximation ratio of the original MaxCut problems is 0.75, while the approximation ratios of the decomposed graphs are on average of 0.96 for both Gurobi and QAOA. With this decomposition, we are able to measure optimal solutions for ten 100-vertex graphs by running single-layer QAOA circuits on the Quantinuum trapped-ion quantum computer H1-1, sampling each circuit only 500 times. This approach is best suited for sparse, particularly k-regular graphs, as k-regular graphs on n vertices can be decomposed into a graph with at most $\frac{nk}{k+1}$ vertices in polynomial time. Further reductions can be obtained with a potential trade-off in computational time. In conclusion, while this paper applies the decomposition method to the MaxCut problem, it can be applied to more general classes of combinatorial optimization problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The Binary Alkali Nitrate and Chloride Phase Diagrams: NaNO{sub 3}-KNO{sub 3}, LiNO{sub 3}-NaNO{sub 3}, LiNO{sub 3}-KNO{sub 3}, and NaCl-KCl

LiNO{sub 3}-NaNO{sub 3}, LiNO{sub 3}-KNO{sub 3,} NaNO{sub 3}-KNO{sub 3}, and NaCl-KCl phase relations were formulated using the regular solution model to obtain desired compositions for their potential application as a heat transfer fluid. The simultaneous nonlinear equations formed were solved numerically using a contour plot technique in Matlab. An algorithm was developed to determine the real roots of the coupled nonlinear equations and subsequent phase diagrams were constructed. The phase diagrams were compared with those predicted using FactSage thermochemical package and literature data from experimental studies. The calculated NaNO{sub 3}-KNO{sub 3} phase diagram shows that this system has a eutectic point at 0.5 mole fraction of KNO{sub 3} with a eutectic temperature of 220.85 °C, while the LiNO{sub 3}-KNO{sub 3} system was found to have a eutectic point at 0.44 mole fraction LiNO{sub 3} at 137 °C. The LiNO{sub 3}-NaNO{sub 3} system shows a eutectic at 0.524 mole fraction LiNO{sub 3} at 192.8 °C, and finally the NaCl-KCl system has a eutectic point at 0.48 mole fraction NaCl at 634 °C. The liquidus and solidus curves obtained fitted close against values obtained from the quasi-chemical model used in FactSage and experimental values from the literature. This study showed that the regular solution model combined with the contour plots approach can sufficiently describe the liquidus–solidus curves of the alkali binary nitrate and chloride systems and could be a useful method for predicting the phase diagrams for higher order alkali nitrates and chlorides.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Bilayer self-assembly on a hydrophilic, deterministically nano-patterned surface

We present measurements of the in-situ, microscopic architecture of a self-assembled bilayer at the interface between a regularly nano-patterned surface and an aqueous sub-phase using neutron reflectometry. The substrate is patterned with a rectangular array of nano-scaled holes. Because of the high quality of the pattern, using neutron reflectometry, we are able to map the surface-normal density distribution of the patterned silicon, the penetration of water into the pattern, and the distribution of a deposited film inside and outside of the etched holes. In this study, 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC) single bilayers were deposited on the hydrophilic patterned surface. For bilayers deposited either by vesicle fusion (VF) or by the Langmuir Schaefer (L-S) technique, the most consistent model found to fit the data shows that the lipids form bilayer coatings on top of the substrate as well as the bottoms of the holes in an essentially conformal fashion. However, while there is a single bilayer on the unetched silicon surface, the lipids coating the bottoms of the holes form a complex bimodal structure consistent with a rough surface produced by the etching process. This study provides insight into film transfer both outside and inside regular nano-patterned features.

Smith, Gregory Scott↗
DOE OSTI2018

Constructing the Pareto front for multi-objective Markov chains handling a strong Pareto policy approach

In this paper, we present a multi-objective solution of the Pareto front for a certain class of discrete-time ergodic controllable Markov chains. For solving the problem, we transform the original multi-objective problem into an equivalent nonlinear programming problem implementing the Lagrange principle. We then propose to adopt the Tikhonov’s regularization method to ensure the convergence of the cost functions to a unique point into the Pareto front. We show that Pareto policies are characterized as optimal policies. One of the fundamental problems related to the construction of the Pareto front is the existence and characterization of both, Pareto and strong Pareto policies. By introducing the Tikhonov’s regularizator, we ensure the existence of strong Pareto policies. This paper proposes a real solution to this problem. We formulate the original problem considering several constraints: (a) we employ the c-variable method for the introduction of linear constraints over the nonlinear problem and (b) restrict the cost functions, allowing points in the Pareto front to have a small distance from one another. The constraints imposed by the c-variable method make the problem computationally tractable and the restriction imposed by the small distance change ensures the continuation of the Pareto front. The resulting equation in this nonlinear system is an optimization problem for which the necessary and efficient condition of a minimum is solved using the projected gradient method. Moreover, we also prove the convergence conditions and compute the estimate rate of convergence of variables corresponding to the Lagrange principle and the Tikhonov’s regularization, respectively. We provide all the details needed to implement the proposed method in an efficient way. The usefulness of the method is successfully demonstrated by a numerical example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

An efficient cost reduction procedure for bounded-control LQR problems

A novel approach has been developed for approximating the solution to the constrained LQR problem, based on updating the final state and costate of a related regular problem, and on slightly shifting the switching times (the instants when the control meets the constraints). The main result is the expression of a suboptimal control in feedback form using the solution of some compatible Riccati equation. The gradient method is applied to reduce the cost via explicit algebraic formula for its partial derivatives with respect to the hidden final state/costate of the related regular problem and to the switching times. The numerical method is termed efficient because it does not involve integrations of states or cost trajectories, and reduces to its minimum the dimension of the unknown parameters at the final condition. All the relevant objects are calculated from a few auxiliary matrices, which are computed only once. The scheme is here applied to two case studies whose optimal solutions are known. The first example is a two-dimensional model of the ‘cheapest stop of a train’ problem. The second one refers to the temperature control of a metallic strip leaving a multi-stand rolling mill, a problem with a high-dimensional state.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Improved pore network models to simulate single-phase flow in porous media by coupling with lattice Boltzmann method

In this paper, different pore network models to simulate single-phase flow in porous media are built and their accuracy is evaluated. In addition to the conventional pore network model (CPNM) which consists of regular pore bodies and throat bonds, three improved pore network models (IPNMs) are developed allowing to better describing the real pore and throat geometry. The first improved pore network model (IPNM1) replaces the regular throat bond with a throat bond showing the real throat cross section. The second improvement (IPNM2) uses a series of sub-throat bonds with varying cross sections to better describe the real throat geometry, which is firstly proposed in this paper. The third model (IPNM3) extracts the real pore-throat-pore geometry without simplification. The conductance of fluid flow through these more realistic throat bonds is calculated by the lattice Boltzmann method (LBM). The accuracy and computational efficiency of the different pore network models are evaluated taking the LBM simulation over the whole porous medium as reference solution. The global permeability and detailed pressure distributions in the pores for the different pore network models are validated. The results show that the accuracy of the pore network model increases from CPNM to IPNM3, but at the expense of increasing computational cost. This study suggests that IPNM3 can replace a whole-domain LBM simulation with similar accuracy but much lower computational cost. As a first-order approximation the newly proposed IPNM2 is suggested as good compromise between accuracy and computational cost.

42 ENGINEERING↗