Search NASA⌕ Search

SEARCH · Search NASA

Results for “MOTIVATION”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

Industrial IoT cross-layer forensic investigation

Cross-layer forensic investigation is addressed for Industrial Internet of Things (IIoT) device attacks in Critical Infrastructure (CI) applications. The operational motivation for cross-layer investigation is provided by the desire to directly correlate bit-level network anomaly detection with physical layer (PHY) device connectivity and/or status (normal, defective, attacked, etc.) at the time of attack. The technical motivation for developing cross-layer techniques is motivated by (a) having considerable capability in place for Higher-Layer Digital Forensic Information exploitation—real-time network cyberattack and postattack analysis, (b) having considerably less capability in place for Lowest-Layer PHY Forensic Information exploitation—the PHY domain remains largely under exploited, and (c) considering cyber-physical integration as a means to jointly exploit higher-layer digital and lowest-layer PHY forensic information to maximize investigative benefit in IIoT cyber forensics. A delineation of higher-layer digital and lowest-layer PHY elements is provided for the standard network Open Systems Interconnection model and the specific Perdue Enterprise Reference Architecture commonly used in IIoT Industrial Control System/Supervisory Control and Data Acquisition applications. Finally, a forensics work summary is provided for each delineated area based on selected representative publications and provides the basis for presenting the envisioned cross-layer forensic investigation.

97 MATHEMATICS AND COMPUTING↗

Interval-Valued Rank in Finite Ordered Sets

We consider the concept of rank as a measure of the vertical levels and positions of elements of partially ordered sets (posets). We are motivated by the need for algorithmic measures on large, real-world hierarchically-structured data objects like the semantic hierarchies of ontolog- ical databases. These rarely satisfy the strong property of gradedness, which is required for traditional rank functions to exist. Representing such semantic hierarchies as finite, bounded posets, we recognize the duality of ordered structures to motivate rank functions which respect verticality both from the bottom and from the top. Our rank functions are thus interval-valued, and always exist, even for non-graded posets, providing order homomorphisms to an interval order on the interval-valued ranks. The concept of rank width arises naturally, allowing us to identify the poset region with point-valued width as its longest graded portion (which we call the “spindle”). A standard interval rank function is naturally motivated both in terms of its extremality and on pragmatic grounds. Its properties are examined, including the relation- ship to traditional grading and rank functions, and methods to assess comparisons of standard interval-valued ranks.

Joslyn, Cliff↗

Opportunities for consumer-driven load shifting in commercial and industrial buildings

Commercial and industrial buildings are typically billed for both electricity consumption and peak 15-minute demand. While this rate structure does not motivate consumers to lower the grid peak demand, it does provide strong motivation for shifting load away from the site peak. However, the economic viability of site peak reduction depends greatly on typical building operations and will vary widely from one building to the next. This paper quantifies the potential that various building types have for site peak reduction using a database of 15-minute demand for buildings in Texas. The primary contribution of this paper is the identification of building types that stand to gain the most by exploiting 15-minute peak demand charges. The influence that site peak demand reduction has on the overall grid is also analyzed. This analysis of site peak reduction in buildings leads to several interesting conclusions. For example, site peak reduction is generally most difficult at industrial and healthcare buildings. On the other hand, grade schools (K-12) and hotels may reduce the site peak with relatively little effort. However, even widespread site peak reduction will only have a minimal effect on the overall grid peak. While buildings may obtain cost savings by reducing these transmission and distribution costs, utilities should consider modifying the retail rate structure in order to provide a direct motivation for consumers to reduce wholesale electricity prices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advanced Permanent Magnet Generator Topologies Using Multimaterial Shape Optimization and 3D Printing: Preprint

A vast majority of utility-scale wind turbine generators in the United States are dependent on foreign- sourced rare-earth permanent magnets that are vulnerable to supply chain uncertainties. Many small wind original equipment manufacturers are motivated to pursue continuous improvements to the generator design to lower the material and production costs and improve performance by lowering cogging torque and increasing the efficiency. Traditional design and manufacturing offer limited opportunities. In this work, we demonstrate advanced design approaches for a 15-kW baseline wind turbine generator by making use of recent progress in three-dimensional (3D) printing of polymer- bonded magnets and, electrical and structural steel. We explore three methods of magnet parametrization using Bezier curves resulting in symmetric, asymmetric and multimaterial magnet designs. We employ a multiphysics approach combining parametric computer-aided design modeling, finite- element analysis and targeted sampling to identify novel designs with more opportunities for reducing rare-earth material, improving efficiency and minimizing cogging torque. The results show that asymmetric-pole design and multimaterial-pole designs offer a greater opportunity to minimize rare-earth magnet materials by up to 35% with similar performance as the baseline generator, suggesting newer opportunities with design freedom beyond traditional limits of symmetry and as allowed by 3D printing.

Bezier curves↗

INVESTIGATING BROADBAND VARIABILITY OF THE TeV BLAZAR 1ES 1959+650

We summarize broadband observations of the TeV-emitting blazar 1ES 1959+650, including optical R-band observations by the robotic telescopes Super-LOTIS and iTelescope, UV observations by Swift Ultraviolet and Optical Telescope, X-ray observations by the Swift X-ray Telescope, high-energy gamma-ray observations with the Fermi Large Area Telescope, and very-high-energy (VHE) gamma-ray observations by VERITAS above 315 GeV, all taken between 2012 April 17 and 2012 June 1 (MJD 56034 and 56079). The contemporaneous variability of the broadband spectral energy distribution is explored in the context of a simple synchrotron self Compton (SSC) model. In the SSC emission scenario, we find that the parameters required to represent the high state are significantly different than those in the low state. Motivated by possible evidence of gas in the vicinity of the blazar, we also investigate a reflected emission model to describe the observed variability pattern. This model assumes that the non-thermal emission from the jet is reflected by a nearby cloud of gas, allowing the reflected emission to re-enter the blob and produce an elevated gamma-ray state with no simultaneous elevated synchrotron flux. The model applied here, although not required to explain the observed variability pattern, represents one possible scenario which can describe the observations. As applied to an elevated VHE state of 66% of the Crab Nebula flux, observed on a single night during the observation period, the reflected emission scenario does not support a purely leptonic non-thermal emission mechanism. The reflected emission model does, however, predict a reflected photon field with sufficient energy to enable elevated gamma-ray emission via pion production with protons of energies between 10 and 100 TeV.

79 ASTRONOMY AND ASTROPHYSICS↗

Anomalous feedback and negative domain wall resistance

Magnetic induction can be regarded as a negative feedback effect, where the motive-force opposes the change of magnetic flux that generates the motive-force. In artificial electromagnetics emerging from spintronics, however, this is not necessarily the case. In this paper, by studying the current-induced domain wall dynamics in a cylindrical nanowire, we show that the spin motive-force exerting on electrons can either oppose or support the applied current that drives the domain wall. The switching into the anomalous feedback regime occurs when the strength of the dissipative torque β is about twice the value of the Gilbert damping constant α. Finally, the anomalous feedback manifests as a negative domain wall resistance, which has an analogy with the water turbine.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Long-lived particles at the energy frontier: the MATHUSLA physics case

In this review, we examine the theoretical motivations for long-lived particle (LLP) signals at the LHC in a comprehensive survey of standard model (SM) extensions. LLPs are a common prediction of a wide range of theories that address unsolved fundamental mysteries such as naturalness, dark matter, baryogenesis and neutrino masses, and represent a natural and generic possibility for physics beyond the SM (BSM). In most cases the LLP lifetime can be treated as a free parameter from the m scale up to the Big Bang Nucleosynthesis limit of m. Neutral LLPs with lifetimes above 100 m are particularly difficult to probe, as the sensitivity of the LHC main detectors is limited by challenging backgrounds, triggers, and small acceptances. MATHUSLA is a proposal for a minimally instrumented, large-volume surface detector near ATLAS or CMS. It would search for neutral LLPs produced in HL-LHC collisions by reconstructing displaced vertices (DVs) in a low-background environment, extending the sensitivity of the main detectors by orders of magnitude in the long-lifetime regime. We study the LLP physics opportunities afforded by a MATHUSLA-like detector at the HL-LHC, assuming backgrounds can be rejected as expected. We develop a model-independent approach to describe the sensitivity of MATHUSLA to BSM LLP signals, and compare it to DV and missing energy searches at ATLAS or CMS. We then explore the BSM motivations for LLPs in considerable detail, presenting a large number of new sensitivity studies. While our discussion is especially oriented towards the long-lifetime regime at MATHUSLA, this survey underlines the importance of a varied LLP search program at the LHC in general. By synthesizing these results into a general discussion of the top–down and bottom-up motivations for LLP searches, it is our aim to demonstrate the exceptional strength and breadth of the physics case for the construction of the MATHUSLA detector.

baryogenesis↗

WIMPs at the galactic center

Simple models of weakly interacting massive particles (WIMPs) predict dark matter annihilations into pairs of electroweak gauge bosons, Higgses or tops, which through their subsequent cascade decays produce a spectrum of gamma rays. Intriguingly, an excess in gamma rays coming from near the Galactic center has been consistently observed in Fermi data. A recent analysis by the Fermi collaboration confirms these earlier results. Taking into account the systematic uncertainties in the modelling of the gamma ray backgrounds, we show for the first time that this excess can be well fit by these final states. In particular, for annihilations to (WW, ZZ, hh, tt{sup -bar}), dark matter with mass between threshold and approximately (165, 190, 280, 310) GeV gives an acceptable fit. The fit range for bb{sup -bar} is also enlarged to 35 GeV≲m{sub χ}≲165 GeV. These are to be compared to previous fits that concluded only much lighter dark matter annihilating into b, τ, and light quark final states could describe the excess. We demonstrate that simple, well-motivated models of WIMP dark matter including a thermal-relic neutralino of the MSSM, Higgs portal models, as well as other simplified models can explain the excess.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Phenomenological aspects of no-scale inflation models

We discuss phenomenological aspects of inflationary models wiith a no-scale supergravity Kähler potential motivated by compactified string models, in which the inflaton may be identified either as a Kähler modulus or an untwisted matter field, focusing on models that make predictions for the scalar spectral index n{sub s} and the tensor-to-scalar ratio r that are similar to the Starobinsky model. We discuss possible patterns of soft supersymmetry breaking, exhibiting examples of the pure no-scale type m{sub 0} = B{sub 0} = A{sub 0} = 0, of the CMSSM type with universal A{sub 0} and m{sub 0} ≠ 0 at a high scale, and of the mSUGRA type with A{sub 0} = B{sub 0} + m{sub 0} boundary conditions at the high input scale. These may be combined with a non-trivial gauge kinetic function that generates gaugino masses m{sub 1/2} ≠ 0, or one may have a pure gravity mediation scenario where trilinear terms and gaugino masses are generated through anomalies. We also discuss inflaton decays and reheating, showing possible decay channels for the inflaton when it is either an untwisted matter field or a Kähler modulus. Reheating is very efficient if a matter field inflaton is directly coupled to MSSM fields, and both candidates lead to sufficient reheating in the presence of a non-trivial gauge kinetic function.

79 ASTRONOMY AND ASTROPHYSICS↗

Direct detection signatures of self-interacting dark matter with a light mediator

Self-interacting dark matter (SIDM) is a simple and well-motivated scenario that could explain long-standing puzzles in structure formation on small scales. If the required self-interaction arises through a light mediator (with mass ∼10 MeV) in the dark sector, this new particle must be unstable to avoid overclosing the universe. The decay of the light mediator could happen due to a weak coupling of the hidden and visible sectors, providing new signatures for direct detection experiments. The SIDM nuclear recoil spectrum is more peaked towards low energies compared to the usual case of contact interactions, because the mediator mass is comparable to the momentum transfer of nuclear recoils. We show that the SIDM signal could be distinguished from that of DM particles with contact interactions by considering the time-average energy spectrum in experiments employing different target materials, or the average and modulated spectra in a single experiment. Using current limits from LUX and SuperCDMS, we also derive strong bounds on the mixing parameter between hidden and visible sector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Non-Abelian fermionization and fractional quantum Hall transitions

There has been a recent surge of interest in dualities relating theories of Chern-Simons gauge fields coupled to either bosons or fermions within the condensed matter community, particularly in the context of topological insulators and the half-filled Landau level. Here, we study the application of one such duality to the long-standing problem of quantum Hall interplateaux transitions. The key motivating experimental observations are the anomalously large value of the correlation length There has been a recent surge of interest in dualities relating theories of Chern-Simons gauge fields coupled to either bosons or fermions within the condensed matter community, particularly in the context of topological insulators and the half-filled Landau level. Here, we study the application of one such duality to the long-standing problem of quantum Hall inter-plateaux transitions. The key motivating experimental observations are the anomalously large value of the correlation length exponent $\nu \approx 2.3$ and that $\nu$ is observed to be super-universal, i.e., the same in the vicinity of distinct critical points [S.L. Sondhi et al., Rev. Mod. Phys. \textbf{69}, 315 (1997)]. Duality motivates effective descriptions for a fractional quantum Hall plateau transition involving a Chern-Simons field with $U(N_c)$ gauge group coupled to $N_f = 1$ fermion. We study one class of theories in a controlled limit where $N_f \gg N_c$ and calculate $\nu$ to leading non-trivial order in the absence of disorder. Although these theories do not yield an anomalously large exponent $\nu$ within the large $N_f \gg N_c$ expansion, they do offer a new parameter space of theories that is apparently different from prior works involving abelian Chern-Simons gauge fields [X.-G. Wen and Y.-S. Wu, Phys. Rev. Lett. \textbf{70}, 1501 (1993); W. Chen. et al., Phys. Rev. B. \textbf{48}, 13749 (1993)].

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Axion dark matter experiment: Run 1B analysis details

Searching for axion dark matter, the ADMX Collaboration acquired data from January to October 2018, over the mass range 2.81–3.31 μeV, corresponding to the frequency range 680–790 MHz. Using an axion haloscope consisting of a microwave cavity in a strong magnetic field, the ADMX experiment excluded Dine-Fischler-Srednicki-Zhitnisky (DFSZ) axions at 90% confidence level and 100% dark matter density over this entire frequency range, except for a few gaps due to mode crossings. This paper explains the full ADMX analysis for run 1B, motivating analysis choices informed by details specific to this run.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Simulations of axion minihalos

The axion, motivated as a solution to the strong CP problem, is also a viable dark matter candidate. The axion field takes random values in causally disconnected regions if the symmetry breaking that establishes the particle occurs after inflation, leading to white-noise density fluctuations at low wave numbers and forming dense minihalos with sub-planetary masses subsequently. There have been two recent proposals that appear capable of testing this scenario, namely using pulsar timing arrays and studying cosmological microlensing caustics. Motivated by these proposals, we use N-body simulations to study the formation of substructures from white-noise density fluctuations. The density profiles of our relaxed axion minihalos can be described by the Navarro–Frenk–White profile, and the minihalos’ concentration number agrees well with a simple, physically-motivated model. We develop a semi-analytic formula to fit the mass function from our simulation, which agrees broadly at different redshifts and only differs at factor of two level from classic halo mass functions. This analytic mass function allows us to consider uncertainties in the post-inflation axion scenario, as well as extrapolate our high-redshift simulations results to the present. Our work estimates the present-day abundance of axion substructures, as is necessary for predicting their effect on cosmological microlensing caustics and pulsar timing. Our calculations suggest that if pulsar timing and microlensing probes can reach recent sensitivity forecasts, they may be sensitive to the post-inflation axion dark matter scenario, even when accounting for uncertainties pertaining to axion strings. For pulsar timing, the most significant caveat is whether axion minihalos are disrupted by stars, which our estimates show is mildly important at the most relevant masses. In conclusion, as our gravitational simulations are scale invariant, the results can be extended to models where the dark matter is comprised of other axion-like particles and even clusters of primordial black holes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Experiments and Project-Based Enhancements for STEM Learning

Motivating K-12 students to pursue careers in science, technology, engineering, and mathematics (STEM) is an effort that requires consistent engagement. Throughout the K-12 student timeline, STEM educators need to continuously pivot their teaching and update their educational materials to motivate the next generation of students. Once students begin their undergraduate education, university professors need to encourage them to consider pursuing graduate studies to ensure that a qualified future workforce can be developed for research and teaching. In this paper, we present our work on developing STEM materials for K-12 student engagement. Our K-12 materials target the grid integration of hydrogen assets that are suitable to engage students in the classroom. Our undergraduate materials target hands-on projects and collaboration with industry to connect classroom learning with real-world applications and needs in renewable energy. Our work leverages available open-source models and tools to create projects for undergraduate students and motivate their interest in pursuing research topics in graduate-level education.

ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimal Storage Response to Utility Tariff Structures and Potential Use of Capacity Charges

Energy storage is increasingly being deployed in behind-the-meter use cases, partially in response to falling lithium-ion prices and new utility tariff structures. Utilities are grappling with new tariff design in the presence of distributed energy resources (DER), trying to motivate, fairly price the contribution of, and, in some cases, discourage, certain operation of DER. There are opportunities for energy storage under emerging tariff structures, but utility net load management objectives for storage remain unclear. Diverse tariff structures motivate the use of energy storage to provide one or a combination of: energy arbitrage, energy shifting, solar self-consumption, and import shaving. This paper formulates a linear optimization to demonstrate the optimal storage tariff response, examining customer net load metrics under diverse utility tariff structures, such as time-of-use, net metering, feed-in tariffs, zero export tariffs, and demand charges. A key contribution of this paper is the introduction and examination of a capacity charge as mechanism that can both motivate reductions in both peak import, and exports, along with greater load levelling.

behind-the-meter↗

Progress on Understanding Rayleigh–Taylor Flow and Mixing Using Synergy Between Simulation, Modeling, and Experiment

Simultaneous advances in numerical methods and computing, theoretical techniques, and experimental diagnostics have all led independently to better understanding of Rayleigh–Taylor (RT) instability, turbulence, and mixing. In particular, experiments have provided significant motivation for many simulation and modeling studies, as well as validation data. Numerical simulations have also provided data that is not currently measurable or very difficult to measure accurately in RT unstable flows. Thus, simulations have also motivated new measurements in this class of buoyancy-driven flows. This overview discusses simulation and modeling studies synergistic with experiments and examples of how experiments have motivated simulations and models of RT instability, flow, and mixing. First, a brief summary of measured experimental and calculated simulation quantities, of experimental approaches, and of issues and challenges in the simulation and modeling of RT experiments is presented. Implicit large-eddy, direct numerical, and large-eddy simulations validated using RT experimental data are then discussed. This is followed by a discussion of modeling using analytical, modal, buoyancy–drag, and turbulent transport models of RT mixing experiments. The discussion will focus on three-dimensional RT mixing arising from multimode perturbations. Finally, this focused review concludes with a perspective on future simulation, modeling, and experimental directions for further research. Research in simulation and modeling of RT unstable flows, coupled with experiments, has made significant progress over the past several decades. This overview serves as an opportunity to both discuss progress and to stimulate future research on simulation and modeling of this unique class of hydrodynamically unstable turbulent flows.

42 ENGINEERING↗