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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

On the v-representability of ensemble densities of electron systems

Analogously to the case at zero temperature, where the density of the ground state of an interacting many-particle system determines uniquely (within an arbitrary additive constant) the external potential acting on the system, the thermal average of the density over an ensemble defined by the Boltzmann distribution at the minimum of the thermodynamic potential, or the free energy, determines the external potential uniquely (and not just modulo a constant) acting on a system described by this thermodynamic potential or free energy. The study describes a formal procedure that generates the domain of a constrained search over general ensembles (at zero or elevated temperatures) that lead to a given density, including as a special case a density thermally averaged at a given temperature, and in the case of a v-representable density determines the external potential leading to the ensemble density. As an immediate consequence of the general formalism, the concept of v-representability is extended beyond the hitherto discussed case of ground state densities to encompass excited states as well. Specific application to thermally averaged densities solves the v-representability problem in connection with the Mermin functional in a manner analogous to that in which this problem was recently settled with respect to the Hohenberg and Kohn functional. Finally, the main formalism is illustrated with numerical results for ensembles of one-dimensional, non-interacting systems of particles under a harmonic potential.

36 MATERIALS SCIENCE↗
NASA NTRS1998

Pattern Search Methods for Linearly Constrained Minimization

We extend pattern search methods to linearly constrained minimization. We develop a general class of feasible point pattern search algorithms and prove global convergence to a Karush-Kuhn-Tucker point. As in the case of unconstrained minimization, pattern search methods for linearly constrained problems accomplish this without explicit recourse to the gradient or the directional derivative. Key to the analysis of the algorithms is the way in which the local search patterns conform to the geometry of the boundary of the feasible region.

Lewis, Robert Michael↗
NASA NTRS2011

Directional Limits on Persistent Gravitational Waves Using LIGO S5 Science Data

The gravitational-wave (GW) sky may include nearby pointlike sources as well as astrophysical and cosmological stochastic backgrounds. Since the relative strength and angular distribution of the many possible sources of GWs are not well constrained, searches for GW signals must be performed in a model-independent way. To that end we perform two directional searches for persistent GWs using data from the LIGO S5 science run: one optimized for pointlike sources and one for arbitrary extended sources. The latter result is the first of its kind. Finding no evidence to support the detection of GWs, we present 90% confidence level (CL) upper-limit maps of GW strain power with typical values between 2 - 20 X 10 (exp -50) strain2Hz(exp -1) and 5 - 35 X 10 (exp -49) strain2Hz(exp -1)/sr for pointlike and extended sources respectively. The limits on pointlike sources constitute a factor of 30 improvement over the previous best limits. We also set 90% CL limits on the narrow-band root-mean-square GW strain from interesting targets including Sco X-1, SN1987A and the Galactic Center as low as approximately equal 7 X 10(exp -25) in the most sensitive frequency range near 160Hz. These limits are the most constraining to date and constitute a factor of 5 improvement over the previous best limits.

Abadie, J.↗
DOE OSTI2016

Pre-equilibrium dynamics and heavy-ion observables

To bracket the importance of the pre-equilibrium stage on relativistic heavy-ion collision observables, we compare simulations where it is modeled by either free-streaming partons or fluid dynamics. These cases implement the assumptions of extremely weak vs. extremely strong coupling in the initial collision stage. Accounting for flow generated in the pre-equilibrium stage, we study the sensitivity of radial, elliptic and triangular flow on the switching time when the hydrodynamic description becomes valid. Using the hybrid code iEBE-VISHNU [1] we perform a multi-parameter search, constrained by particle ratios, integrated elliptic and triangular charged hadron flow, the mean transverse momenta of pions, kaons and protons, and the second moment of the proton transverse momentum spectrum, to identify optimized values for the switching time \tau_s from pre-equilibrium to hydrodynamics, the specific shear viscosity eta/s, the normalization factor of the temperature-dependent specific bulk viscosity (zeta/s)(T), and the switching temperature T_sw from viscous hydrodynamics to the hadron cascade UrQMD. With the optimized parameters, we predict and compare with experiment the p_T -distributions of pi, K, p, Lambda, Xi and Omega yields and their elliptic flow coefficients, focusing specifically on the mass-ordering of the elliptic flow for protons and Lambda hyperons which is incorrectly described by VISHNU without pre-equilibrium flow.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

On extending Kohn-Sham density functionals to systems with fractional number of electrons

Here, we analyze four ways of formulating the Kohn-Sham (KS) density functionals with a fractional number of electrons, through extending the constrained search space from the Kohn-Sham and the generalized Kohn-Sham (GKS) non-interacting $\mathcal{v}$-representable density domain for integer systems to four different sets of densities for fractional systems. In particular, these density sets are (I) ensemble interacting N -representable densities, (II) ensemble non-interacting N -representable densities, (III) non-interacting densities by the Janak construction, and (IV) non-interacting densities whose composing orbitals satisfy the Aufbau occupation principle. By proving the equivalence of the underlying first order reduced density matrices associated with these densities, we show that sets (I), (II), and (III) are equivalent, and all reduce to the Janak construction. Moreover, for functionals with the ensemble v-representable assumption at the minimizer, (III) reduces to (IV) and thus justifies the previous use of the Aufbau protocol within the (G)KS framework in the study of the ground state of fractional electron systems, as defined in the grand canonical ensemble at zero temperature. By further analyzing the Aufbau solution for different density functional approximations (DFAs) in the (G)KS scheme, we rigorously prove that there can be one and only one fractional occupation for the Hartree Fock functional, while there can be multiple fractional occupations for general DFAs in the presence of degeneracy. This has been confirmed by numerical calculations using the local density approximation as a representative of general DFAs. This work thus clarifies important issues on density functional theory calculations for fractional electron systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Plug & play directed evolution of proteins with gradient-based discrete MCMC

Abstract A long-standing goal of machine-learning-based protein engineering is to accelerate the discovery of novel mutations that improve the function of a known protein. We introduce a sampling framework for evolving proteins in silico that supports mixing and matching a variety of unsupervised models, such as protein language models, and supervised models that predict protein function from sequence. By composing these models, we aim to improve our ability to evaluate unseen mutations and constrain search to regions of sequence space likely to contain functional proteins. Our framework achieves this without any model fine-tuning or re-training by constructing a product of experts distribution directly in discrete protein space. Instead of resorting to brute force search or random sampling, which is typical of classic directed evolution, we introduce a fast Markov chain Monte Carlo sampler that uses gradients to propose promising mutations. We conduct in silico directed evolution experiments on wide fitness landscapes and across a range of different pre-trained unsupervised models, including a 650 M parameter protein language model. Our results demonstrate an ability to efficiently discover variants with high evolutionary likelihood as well as estimated activity multiple mutations away from a wild type protein, suggesting our sampler provides a practical and effective new paradigm for machine-learning-based protein engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

EvoProtGrad (Directed Evolution for Proteins with Gradients) [SWR-23-48]

A Python package for directed evolution on a protein sequence with gradient-based discrete Markov chain monte carlo (MCMC). Users are able to compose custom models that map sequence to function with pretrained models, including protein language models (PLMs), to guide and constrain search. Our package natively integrates with the HuggingFace platform and supports PLMs from transformers. Our MCMC sampler identifies promising amino acids to mutate via model gradients taken with respect to the input (i.e., sensitivity analysis). We allow users to compose their own custom target function for MCMC by leveraging the Product of Experts MCMC paradigm. Each model is an "expert" that contributes its own knowledge about the protein's fitness landscape to the overall target function. The sampler is designed to be more efficient and effective than brute force and random search while maintaining most of the generality and flexibility. Additional information can be found in the related publication: https://iopscience.iop.org/article/10.1088/2632-2153/accacd

Emami, Patrick↗
DOE OSTI2025

BAMBAM (The Behavior and Advanced Mobility Big Access Model) [SWR-25-123]

Access modeling toolkit for Rust built on the RouteE Compass energy-aware route planner. The Behavior and Advanced Mobility Big Access Model (BAMBAM) is a mobility research platform for scalable access modeling. The process begins with a grid defined at some spatial granularity (e.g., census block or 1 km grid) and a variety of travel configurations. For each grid cell and configuration, the platform executes constrained searches, uses the results to index points of interest (POI), and aggregates the findings to the grid level. It provides researchers access through R or Python running on HPC. The platform automates the import and merging of datasets from a variety of sources including data.gov (with automatic merging of Tiger/Lines geometries), OpenStreetMaps, OvertureMaps, and GTFS. It is built upon RouteE Compass, a scalable, energy-aware route planner written in Rust, extended to model multiple travel modes.

Fitzgerald, Robert [National Renewable Energy Labo↗
NASA NTRS1986

Automated remote sensing of sea ice using synthetic aperture radar

Two techniques for automated sea ice tracking: image pyramids (hierarchical correlation) and feature tracking were applied to a pair of SEASAT SAR sea ice images. The results compare well with each other and manually tracked estimates of the ice velocity field. Refinement of the image pyramid technique should include removal of a small number of erroneous velocity vectors using constraints dependent on correlation coefficient, near neighbor velocities, and velocity gradients. Estimates of sea ice velocity are successfully obtained over limited areas using the boundary segment tracking technique. Refinement of the feature tracking technique should include use of pressure ridge features, constrained search, and relaxation techniques.

Vesecky, J. F.↗
NASA NTRS2010

Impact of Merger/Ringdown on SMBHB Parameter Estimation with LISA

The Laser Interferometer Space Antenna (LISA) will measure gravitational waves from the inspiral and merger of supermassive black hole bina ries (SMBHBs) at high redshift with large signal to noise. These meas urements will allow extraction of the SMBHB parameters (component mas ses, spins, binary orbital parameters, sky location, and distance) wi th exquisite accuracy. Here we present a study of the impact on measu red parameter precision from the inclusion of accurate waveforms for the merger/ringdown portion of the signal. we focus specifically on s ky-position and luminosity distance, the most important parameters fo r constraining searches for potential electromagnetic counterparts to SMBHB merger events.

Thorpe, James I.↗
NASA NTRS1996

Pattern Search Algorithms for Bound Constrained Minimization

We present a convergence theory for pattern search methods for solving bound constrained nonlinear programs. The analysis relies on the abstract structure of pattern search methods and an understanding of how the pattern interacts with the bound constraints. This analysis makes it possible to develop pattern search methods for bound constrained problems while only slightly restricting the flexibility present in pattern search methods for unconstrained problems. We prove global convergence despite the fact that pattern search methods do not have explicit information concerning the gradient and its projection onto the feasible region and consequently are unable to enforce explicitly a notion of sufficient feasible decrease.

Lewis, Robert Michael↗
DOE OSTI2018

Broadening Dark Matter Searches at the LHC: Mono-X versus Darkonium Channels

Current searches for dark matter at the LHC focus on mono-X signatures: the production of dark matter in association with a Standard Model (SM) particle. The simplest benchmark introduces a massive spin-1 mediator, the Z$^{′}$ boson, between the dark matter χ and the SM. Limits derived from mono-X channels are most effective when the mediator can decay into two on-shell dark matter particles: M$_{Z}$′ ≳ 2M$_{χ}$. We broaden the experimental reach into the complementary region, where the Z$^{′}$ mediator is much lighter than the dark matter. In this scenario the Z$^{′}$ mediates an effective long-range force between the dark matter, thereby facilitating the formation of darkonium bound states, as is common in many dark sector models. The darkonium becomes active when M$_{χ}$> M$_{Z}$′/α$_{eff}$ , where α$_{eff}$ is the effective fine-structure constant in the dark sector. Moreover, the darkonium could decay back into SM quarks, without producing missing transverse momentum in the detector. Considering multijet final states, we reinterpret existing searches to constrain the simple Z$^{′}$ benchmark beyond the region probed by mono-X searches. Assuming a baryonic Z$^{′}$ mediator and a Dirac dark matter, direct detection bounds can be loosened by giving a small Majorana mass to the dark matter. We also consider the interplay between mono-X and darkonium channels at future high energy colliders, which is at the frontier of probing the model parameter space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2006

Improving Grasp Skills Using Schema Structured Learning

Abstract In the control-based approach to robotics, complex behavior is created by sequencing and combining control primitives. While it is desirable for the robot to autonomously learn the correct control sequence, searching through the large number of potential solutions can be time consuming. This paper constrains this search to variations of a generalized solution encoded in a framework known as an action schema. A new algorithm, SCHEMA STRUCTURED LEARNING, is proposed that repeatedly executes variations of the generalized solution in search of instantiations that satisfy action schema objectives. This approach is tested in a grasping task where Dexter, the UMass humanoid robot, learns which reaching and grasping controllers maximize the probability of grasp success.

Platt, Robert↗
NASA NTRS1975

Transfer-function-parameter estimation from frequency response data: A FORTRAN program

A FORTRAN computer program designed to fit a linear transfer function model to given frequency response magnitude and phase data is presented. A conjugate gradient search is used that minimizes the integral of the absolute value of the error squared between the model and the data. The search is constrained to insure model stability. A scaling of the model parameters by their own magnitude aids search convergence. Efficient computer algorithms result in a small and fast program suitable for a minicomputer. A sample problem with different model structures and parameter estimates is reported.

Seidel, R. C.↗
DOE OSTI2023

Theories and Constraints for Massive Higher Spins (Final Technical Report)

The goal of this project was to develop methods for constraining the scattering amplitudes of interacting theories containing massive higher spin particles, and to apply these methods to search for, constrain, and apply theories containing massive high spins. During the 3 year term of the project, 15 papers containing results from the project were published in peer reviewed journals. Highlights of these results include: proofs of the best possible strong coupling scales for theories with massive spin 2 particles, causality constraints on couplings in such theories, the discovery of new effective field theories with extended shift symmetries on curved space, the discovery of a new symmetry of the decoupling limit of massive gravity, a study of the possible shapes of graviton non-gaussianities during inflation, classification results of supersymmetric partially massless fields, and the development of the geometric bootstrap, a novel method to generate new mathematical results about the spectrum of various Laplacian operators on closed Einstein manifolds.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1995

Genetic algorithms as global random search methods

Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that that schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solution and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.

Peck, Charles C.↗
NASA NTRS1995

Genetic algorithms as global random search methods

Genetic algorithm behavior is described in terms of the construction and evolution of the sampling distributions over the space of candidate solutions. This novel perspective is motivated by analysis indicating that the schema theory is inadequate for completely and properly explaining genetic algorithm behavior. Based on the proposed theory, it is argued that the similarities of candidate solutions should be exploited directly, rather than encoding candidate solutions and then exploiting their similarities. Proportional selection is characterized as a global search operator, and recombination is characterized as the search process that exploits similarities. Sequential algorithms and many deletion methods are also analyzed. It is shown that by properly constraining the search breadth of recombination operators, convergence of genetic algorithms to a global optimum can be ensured.

Peck, Charles C.↗