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 163 records · Page 9

Terrestrial density of strongly-coupled relics

The simplest cosmologies motivate the consideration of dark matter subcomponents that interact significantly with normal matter. Moreover, such strongly coupled relics may have evaded detection to date if upon encountering the Earth they rapidly thermalize down to terrestrial temperatures, T ⊕ ∼ 300 K ∼ 25 meV , well below the thresholds of most existing dark matter detectors. This shedding of kinetic energy implies a drastic enhancement to the local density, motivating the consideration of alternative detection techniques sensitive to a large density of slowly moving dark matter particles. In this work, we provide a rigorous semianalytic derivation of the terrestrial overdensities of strongly coupled relics, with a particular focus on millicharged particles (MCPs). We go beyond previous studies by incorporating improved estimates of the MCP-atomic scattering cross section, new contributions to the terrestrial density of sub-GeV relics that are independent of the Earth’s gravitational field, and local modifications that can arise due to the cryogenic environments of precision sensors. We also generalize our analysis in order to estimate the terrestrial density of thermalized MCPs that are produced from the collisions of high-energy cosmic rays and become bound by the Earth’s electric field. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DESI 2024: Constraints on physics-focused aspects of dark energy using DESI DR1 BAO data

Baryon acoustic oscillation data from the first year of the Dark Energy Spectroscopic Instrument (DESI) provide near percent-level precision of cosmic distances in seven bins over the redshift range z=0.1–4.2. Here, this paper is the follow-up to the original DESI BAO cosmology paper [A. G. Adame et al. (DESI Collaboration), arXiv:2404.03002], which considered the conventional w 0 w a cold dark matter (CDM) model. We use the novel DESI data, together with other cosmic probes, to constrain the background expansion history using some well-motivated physical classes of dark energy. In particular, we explore three physics-focused behaviors of dark energy from the equation of state and energy density perspectives: the thawing class (matching many simple quintessence potentials), emergent class (where dark energy comes into being recently, as in phase transition models), and mirage class [where phenomenologically the distance to cosmic microwave background (CMB) last scattering is close to that from a cosmological constant Λ despite dark energy dynamics]. All three classes fit the data at least as well as Λ ⁢CDM, and indeed can improve on it by Δ⁢χ 2 ≈ –5 to –17 for the combination of DESI BAO with CMB and supernova data while having one more parameter. The mirage class does essentially as well as w 0 ⁢w a CDM and exhibits moderate to strong Bayesian evidence preference with respect to Λ⁢ CDM. These classes of dynamical behaviors highlight worthwhile avenues for further exploration into the nature of dark energy.

79 ASTRONOMY AND ASTROPHYSICS↗

Dynamics-based halo model for large scale structure

Accurate modeling of the one-to-two halo transition has long been difficult to achieve. Here, we demonstrate that physically motivated halo definitions that respect the bimodal phase-space distribution of dark matter particles near halos resolves this difficulty. Specifically, the two phase-space components are overlapping and correspond to (1) particles orbiting the halo and (2) particles infalling into the halo for the first time. Motivated by this decomposition, García et al. [Mon. Not. R. Astron. Soc. 521, 2464 (2023)] advocated for defining halos as the collection of particles orbiting their self-generated potential. This definition identifies the traditional one-halo term of the halo-mass correlation function with the distribution of orbiting particles around a halo, while the two-halo term governs the distribution of infalling particles. We use dark matter simulations to demonstrate that the distribution of orbiting particles is finite and can be characterized by a single physical scale 𝑟 h , which we refer to as the halo radius. The two-halo term is described using a simple yet accurate empirical model based on the Zel’dovich correlation function. We further demonstrate that the halo radius imprints itself on the distribution of infalling particles at small scales. Our final model for the halo-mass correlation function is accurate at the ≈ 2% level for 𝑟∈ [0.1, 50] ℎ −1 Mpc. The Fourier transform of our best-fit model describes the halo-mass power spectrum with comparable accuracy for 𝑘 ∈ [0.06, 6.0] ℎ Mpc −1 .

79 ASTRONOMY AND ASTROPHYSICS↗

Quantum computing for energy correlators

In recent years, energy correlators have emerged as powerful observables for probing the fragmentation dynamics of high-energy collisions. We introduce the first numerical strategy for calculating energy correlators using the Hamiltonian lattice approach, providing access to the intriguing nonperturbative dynamics of these observables. Furthermore, motivated by rapid advances in quantum computing hardware and algorithms, we propose a quantum algorithm for calculating energy correlators in quantum field theories. This algorithm includes ground state preparation, the application of source, sink, energy flux and real-time evolution operators, and the Hadamard test. We validate our approach by applying it to the SU(2) pure gauge theory in 2 + 1 dimensions on 3 × 3 and 5 × 5 honeycomb lattices with 𝑗 max = $\frac{1}{2}$ at various couplings, utilizing both classical methods and the quantum algorithm, the latter tested using the IBM emulator for specific configurations. The results are consistent with the expected behavior of the strong coupling regime and motivate a more comprehensive study to probe the confinement dynamics across the weak and strong coupling regimes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Supermassive Black Holes, Ultralight Dark Matter, and Gravitational Waves from a First Order Phase Transition

We report that the formation of ultra rare supermassive black holes (SMBHs), with masses of $\mathcal{O}$(10 9 M ⊙ ), in the first billion years of the Universe remains an open question in astrophysics. At the same time, ultralight dark matter (DM) with mass in the vicinity of $\mathcal{O}$(10 -20 eV) has been motivated by small scale DM distributions. Though this type of DM is constrained by various astrophysical considerations, certain observations could be pointing to modest evidence for it. We present a model with a confining first order phase transition at ~ 10 keV temperatures, facilitating production of $\mathcal{O}$(10 9 M ⊙ ) primordial SMBHs. Such a phase transition can also naturally lead to the implied mass for a motivated ultralight axion DM candidate, suggesting that SMBHs and ultralight DM may be two sides of the same cosmic coin. We consider constraints and avenues to discovery from superradiance and a modification to N eff . On general grounds, we also expect primordial gravitational waves – from the assumed first order phase transition – characterized by frequencies of $\mathcal{O}$(10 -12 - 10 -9 Hz). This frequency regime is largely uncharted, but could be accessible to pulsar timing arrays if the primordial gravitational waves are at the higher end of this frequency range, as could be the case in our assumed confining phase transition.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

How to falsify string theory at a collider

The string landscape accommodates a broad range of possible effective field theories. This poses a challenge for extracting verifiable predictions as well as falsifiable signatures of string theory. Motivated by these considerations, in this work we observe that all known stringy standard models support only low-dimensional representations of the gauge group. While it is in principle possible to produce contrived models with higher-dimensional representations, these generically appear in a tower of states with lighter ones in lower-dimensional representations, i.e., not in isolation. With this in mind, we consider the phenomenologically well-motivated scenario given by adding a single Majorana field in a real, 𝑛-dimensional representation of 𝑆⁢𝑈⁢(2) 𝐿 with 𝑛≥5 and nothing else . This scenario is not realized in any known string construction, and we conjecture that this is true of string theory in general. Detection of this scenario would thus amount to falsifying the (known) string landscape. We recast existing LHC searches for new electroweak states to extract updated bounds on this class of scenarios. Improved limits from future colliders and dark matter detection experiments provide additional routes to potentially falsifying string theory.

extensions of fermion sector↗

Network Anomaly Detection Using Federated Learning

The internet is turning out to be an integral part of every-one's lives as more and more devices are being connected to serve societal needs. Our work is motivated by two ma-jor observations. Firstly, one drawback of connecting to the network is the threat of network attacks that can compromise users' private information, leading to data loss and adversely affecting productivity. There are several traditional security mechanisms to defend against these attacks, such as firewalls, virtual private networks (VPNs), demilitarized zones (DMZs), and vulnerability scanners. One way to prevent these attacks is early detection and prevention. However, these kinds of architecture do not scale very well because of their centralized nature. Secondly, we observe from heuristics and data set distributions that the majority of the requests made to a server are innocuous. Therefore, almost all server request data sets are highly imbalanced, weighted highly towards the harmless requests.

Marfo, William↗

Advancing the Frontiers of Deep Learning for Low-Dose 3D Cone-Beam CT Reconstruction

X-ray computed tomography (CT) is an important noninvasive medical imaging modality for studying the structural details of internal organs. Image reconstruction in CT is an inverse problem of recovering an object's internal structure from the absorption profile of X-ray beams (sinogram) measured using a detector. The classical variational approach for CT reconstruction minimizes an energy functional using an appropriate iterative algorithm. Motivated by the success of deep learning (DL), researchers have begun to leverage training data and enhanced computing capabilities in recent years to produce high-fidelity reconstructed images. Nonetheless, much of the academic research in DL algorithms for CT has focused primarily on the two-dimensional setting (with simplified forward operators and noise model) for proofs-of-concept, and a comprehensive benchmarking of various classical and data-driven CT reconstruction approaches has not beenundertaken. The key objective of our CT reconstruction grand challenge was to promote methodological advancements for both classical and DL-based approaches for clinical CT with a reasonably accurately simulated 3D CT forward operator and noise model. We have utilized the publicly available LIDC-IDRI dataset and simulated sinograms and FDK images corresponding to two dose levels (clinical- and low-dose, constituting two tracks of the challenge) starting from the normal-dose images as the ground truth. In this paper, we summarize the motivation, context, and results of our challenge, and highlight the future research directions in DL for clinical CT.

X-ray tomography↗

Decentralized Distribution System Restoration with Grid-Forming/Following Inverter-Based Resources

The high penetration of distributed energy resources (DERs) in active distribution systems has posed challenges to the centralized distribution system restoration (DSR) strategies in current practice. On the other hand, the advancement in smart inverter technologies enables the bottom-up restoration capability. This paper is motivated to develop a 3-layered hierarchical framework for decentralized DSR, based on the grid-forming (GFM) and grid-following (GFL) grid-edge inverters. The first layer presents the tertiary control, which determines the load pickup schedule and generation dispatch of DERs, using the alternating direction method of the multipliers algorithm. The second layer consists of two control functions: GFM control, which regulates voltage and frequency, establishing a stable grid for GFL inverters to follow; and GFL control, which regulates the real and reactive power. In the third layer, the primary control is proposed to regulate the inverter voltage and current, which is developed based on the virtual oscillator control (VOC). Furthermore, the developed framework is tested in the modified IEEE 13-node test feeder. Two scenarios of grid-connected and islanded operating modes are designed, and simulation results demonstrate the effectiveness of decentralized DSR strategies for controlling grid-edge inverters to enhance the distribution system resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Model Assumptions and Data Characteristics: Impacts on Domain Adaptation in Building Segmentation

Studies on domain adaptation (DA) for remote sensing (RS) imagery analysis lack consistency in selection and description of evaluation scenarios. Without properly characterizing datasets, model assumptions, and evaluation scenarios, it is difficult to objectively compare DA methods and reach conclusions about their suitability across different applications. With this motivation, this work seeks to empirically assess to which extent the interaction between data characteristics and model assumptions influences the effectiveness of DA methods. Using the widely explored task of building footprint segmentation as a case study, we perform a large-scale study across over 200 DA scenarios that include variations across view angles, areas observed, and sensors used for data acquisition. Rather than adopting different model architectures or optimization criteria, we contrast the performances of two DA methods based on adversarial learning that differ only in their assumptions about source and target domains. Informed by metadata and data characteristics unveiled using traditional computer vision (CV) techniques as well as pretrained deep models, we provide a detailed meta-analysis of experiments highlighting the importance of accurately considering data assumptions for DA in RS segmentation tasks. As demonstrated by a “cherry-picking” exercise, different claims regarding which model is best could be made by selecting different subsets of evaluation scenarios. While well-calibrated assumptions can be beneficial, mismatching assumptions can lead to negative biases in DA applications. Furthermore, this study intends to motivate the community toward more consistent evaluation protocols while providing recommendations and insights toward creating novel benchmark datasets, documenting data characteristics, application-specific knowledge, and model assumptions.

42 ENGINEERING↗

Improved Frequency-Domain Steady-State Modeling of the Dual-Active-Bridge Converter Considering Finite ZVS Transition Time Effects

This article presents an improved analytical modeling (IAM) approach for the dual-active-bridge (DAB) converter in the frequency-domain. Specifically, finite transition times are incorporated into the improved modeling that are significant in DAB converters operated at high frequency. The IAM approach is first motivated by comparing traditional frequency-domain modeling against realistic simulation results in LTspice. Next, the IAM approach is mathematically developed in an iterative fashion, where the conventional frequency-domain approach is used as the initialization of the operational behavior of the converter. Subsequent iterations of the IAM algorithm incorporate finite rise- and falltimes of device output capacitances based on detailed switching behavior analyses, which may considerably perturb the desired modulation parameters (i.e., phase shift and zero states). While the initially proposed IAM approach demonstrates advantages over ideal modeling, it is still shown to exhibit errors when applied to device transitions with significant nonlinearity in parasitic output capacitance. To account for this, a three-slope approximation to the switching transition is then motivated and developed, which enables significantly improved steady-state prediction accuracy. Simulation and experimental results confirm unacceptable inaccuracies associated with the conventional frequency-domain modeling across a wide range of operating conditions, alongside enhanced accuracy provided by the proposed modeling approach.

14 SOLAR ENERGY↗

Identification of Dynamic Force Coefficients for an Additively Manufactured Hermetic Squeeze Film Bearing Support Damper Utilizing a Pass-Through Channel

Abstract The following paper presents breakthrough experimental results for a new hermetic squeeze film damper (HSFD) concept that is integrally designed within an externally pressurized tilting-pad radial gas bearing support. The flexibly damped gas bearing module was designed for a 7.2″ (183 mm) diameter shaft and fabricated using direct metal laser melting (DMLM); also known as additive manufacturing. The bearing and HSFD were sized based on ongoing studies for oil-free supercritical carbon dioxide (sCO2) power turbines in the 8.5 MW–10 MW power range. The development of the new damper concept was motivated by past dynamic testing on HSFD, which generated frequency-dependent stiffness and damping force coefficients. In efforts to eliminate the frequency dependency, a new HSFD architecture was conceived that adds accumulator volumes and a pass-through channel to previously conceived HSFD flow network designs. The other motivation for the work is the need to develop a cost-effective and reliable oil-free bearing technology that is scalable to large power turbomachinery applications. There were several objectives for the following work. The first objective was to successfully design and fabricate a single piece bearing-damper using additive manufacturing, while dimensionally controlling critical design features. The paper discusses the manufacturing steps and shows cut-ups that reveal adequate clearance control capability with internal damper clearances. The second objective was to perform experimental testing with the new HSFD design in efforts to extract stiffness and damping coefficients for excitation frequencies within 20–160 Hz and peak vibration amplitudes between 0.25 mils (6.35 microns) to 1 mil (25.4 microns). The test results for a single HSFD bearing module indicated that the design modifications to the HSFD architecture were successful in eliminating nearly all the frequency dependencies for the stiffness force coefficient. The dynamic tests yielded a stiffness coefficient that varied between 112 klb/in. (19.6 MN/m) and 96 klb/in. (16.8 MN/m). The damping force coefficient however, exhibited relatively more variation with frequency with values residing between 175 lb-s/in. (31 kN-s/m) to 214 lb-s/in. (37 kN-s/m). Finally, the paper advances a three-dimensional fluid-structure interaction (FSI) model using transient finite element analysis (FEA) coupled to a computational fluid dynamics (CFD) model. The FSI analysis performed between 20 Hz and 80 Hz was used to predict the stiffness and damping of the HSFD using a quarter-section model of the damper. The FSI analysis was able to support test results by showing only a 6–7.4% change in the magnitude of force coefficients. Stiffness predictions agree reasonably well with experiments whereas damping is underpredicted.

Engineering↗

DESIGN AND TESTING OF DIMES CARBON ABLATION RODS IN THE DIII-D TOKAMAK

We present the design of ATJ graphite rods developed for ablation experiments under high heat flux (up to 50 MW/m2) in the lower divertor of the DIII-D tokamak, a magnetic plasma confinement device. This work is motivated by the need to test ablation models relevant to carbon-based thermal shields used in high-speed spacecraft atmospheric entries, where the heat fluxes encountered can be comparable to those achieved in the DIII-D divertor plasma. Several different designs for the flowfacing side of the rod are analyzed, including "sharp nose," "blunt," and "concave". The last shape is studied for its potential to lower heat fluxes at the rod surface by increased radiation from trapped neutrals and reduced parallel plasma pressure. We also analyze the possibility of applying a thin (approximately 30 microns) layer of silicon carbide (SiC) to the exposed part of several carbon ablation rods to benchmark its erosion calculations and lifetime predictions. Such calculations are of interest as SiC represents a promising material for both thermal protection systems (TPS) and a fusion plasma-facing material (PFM). Preliminary results from the DIII-D rod ablation experiments are also discussed.

Orlov, Dmitri M.↗

Mesofluidic Oil-Water Separation

Separating flowing multiphase solutions in process at industrial scale is challenging. A rapid continuous approach is desired. These mesofluidic oil-water separation tests were motivated by reports by Dijkshoorn et al [1] who reported separating droplets and particles using displacement with regularly spaced channels using a cross-flow microsieve.. Droplets, including deformable particles, larger than the channel migrate in one direction and thereby deplete in the other direction. Test flowrates were motivated by Burns et al. [4] who showed that separation could occur under laminar conditions, and Pease et al [8, 9] who extended the range to turbulent flow. Testing was conducted using two two-component oil-water mixtures at room temperature. Analysis showed separation of both mineral oils from their oil water mixtures at flowrates from 1-2 L/min and concentrations from 2-10 wt% oil in water.

cloud height, effective cleaning radius, effective↗

From binary to quinary: The rationale and development of GaInAsSbBi for mid- and long-wave infrared sensing applications

Given the added complexity in flux calibration and composition evaluation inherent to quinary alloy growth, what motivates compounding the challenges of III–V-Bi growth with the goal of producing a quinary alloy of GaInAsSbBi for mid- and long-wave infrared sensing applications? Each elemental constituent provides some additional design freedom to achieve the ultimate goal of producing a lattice-matched, bulk random alloy mid-wave infrared III–V material with smooth surface morphology and high optoelectronic quality to enable high performance elevated operating temperatures. Here, this paper reviews the evolution of Bi-containing semiconductor research, focusing on mid- and long-wave infrared materials and highlighting key research findings that motivated the decisions to accept the added complexity in going from binaries like InAs or InSb, to InAsBi, to InAsSbBi, and, finally, to GaInAsSbBi to meet the performance demands of advanced infrared sensing applications.

Webster, Preston T. [Air Force Research Laboratory↗

Optimizing Transmission of Acoustic Signals to Monitor Internal Conditions of Canisters for Dry Storage of Commercial Spent Nuclear Fuel

Safe storage of spent nuclear fuel (SNF) is critical to the nuclear fuel cycle and the future of nuclear energy. In the United States, SNF is stored primarily via two methods regulated by the U.S. Nuclear Regulatory Commission: wet storage in SNF pools and dry storage in dry cask storage systems (DCSSs). After about five years of cooling in spent fuel pools, the fuel assemblies are transferred into DCSSs, and the systems are filled with helium and sealed by welding. Deterioration of conditions inside of a DCSS is reflected in changes in the internal gas properties; this motivates the development of acoustic techniques to monitor internal gas properties, over extended storage periods, using sensors mounted on the exterior of the storage packages. However, a major challenge in collecting acoustic signals is the impedance mismatch between the steel canister shell and the gas. Only a small fraction of the ultrasonic signal can be transmitted through the gas medium. This paper documents experimental studies conducted on a full-scale canister mock-up to capture the gas-borne signals. Damping materials were pasted on the outside, and blocking and unblocking tests were conducted to identify the gas-borne signal. The results show that the excitation frequency plays an important role in maximizing the gas-borne signals. The gas-borne signal was successfully detected at around the theoretical time-of-flight. A high signal-to-noise ratio was achieved in the measurements. Next, the acoustic impedance matching layers were introduced, and the gas signal was drastically improved compared with that using no AIM layers.

Spent nuclear fuel (SNF), Canisters, Internal cond↗

Hunting for Majoranas

Over the past decade, there have been considerable efforts to observe non-abelian quasiparticles in novel quantum materials and devices. These efforts are motivated by the goals of demonstrating quantum statistics of quasiparticles beyond those of fermions and bosons and of establishing the underlying science for the creation of topologically protected quantum bits. In this Review, we focus on efforts to create topological superconducting phases that host Majorana zero modes. We consider the lessons learned from existing experimental efforts, which are motivating both improvements to present platforms and the exploration of new approaches. Although the experimental detection of non-abelian quasiparticles remains challenging, the knowledge gained thus far and the opportunities ahead offer high potential for discovery and advances in this exciting area of quantum physics.

Science & Technology - Other Topics↗

Drug providers’ perspectives on antibiotic misuse practices in eastern Ethiopia: a qualitative study

Objective Antibiotic misuse includes using them to treat colds and influenza, obtaining them without a prescription, not finishing the prescribed course and sharing them with others. Although drug providers are well positioned to advise clients on proper stewardship practices, antibiotic misuse continues to rise in Ethiopia. It necessitates an understanding of why drug providers failed to limit such risky behaviours. This study aimed to explore drug providers’ perspectives on antibiotic misuse practices in eastern Ethiopia. Setting The study was conducted in rural Haramaya district and Harar town, eastern Ethiopia. Design and participants An exploratory qualitative study was undertaken between March and June 2023, among the 15 drug providers. In-depth interviews were conducted using pilot-tested, semistructured questions. The interviews were transcribed verbatim, translated into English and analysed thematically. The analyses considered the entire dataset and field notes. Results The study identified self-medication pressures, non-prescribed dispensing motives, insufficient regulatory functions and a lack of specific antibiotic use policy as the key contributors to antibiotic misuse. We found previous usage experience, a desire to avoid extra costs and a lack of essential diagnostics and antibiotics in public institutions as the key drivers of non-prescribed antibiotic access from private drug suppliers. Non-prescribed antibiotic dispensing in pharmacies was driven by client satisfaction, financial gain, business survival and market competition from informal sellers. Antibiotic misuse in the setting has also been linked to traditional and ineffective dispensing audits, inadequate regulatory oversights and policy gaps. Conclusion This study highlights profits and oversimplified access to antibiotics as the main motivations for their misuse. It also identifies the traditional antibiotic dispensing audit as an inefficient regulatory operation. Hence, enforcing specific antibiotic usage policy guidance that entails an automated practice audit, a responsible office and insurance coverage for persons with financial limitations can help optimise antibiotic use while reducing resistance consequences.

General & Internal Medicine↗