Search NASA⌕ Search

SEARCH · Search NASA

Results for “Mobile computing”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

NVL-C: Static Analysis Techniques for Efficient, Correct Programming of Non-Volatile Main Memory Systems

Computer architecture experts expect that non-volatile memory (NVM) hierarchies will play a more significant role in future systems including mobile, enterprise, and HPC architectures. With this expectation in mind, we present NVL-C: a novel programming system that facilitates the efficient and correct programming of NVM main memory systems. The NVL-C programming abstraction extends C with a small set of intuitive language features that target NVM main memory, and can be combined directly with traditional C memory model features for DRAM. We have designed these new features to enable compiler analyses and run-time checks that can improve performance and guard against a number of subtle programming errors, which, when left uncorrected, can corrupt NVM-stored data. Moreover, to enable recovery of data across application or system failures, these NVL-C features include a flexible directive for specifying NVM transactions. So that our implementation might be extended to other compiler front ends and languages, the majority of our compiler analyses are implemented in an extended version of LLVM's intermediate representation (LLVM IR). We evaluate NVL-C on a number of applications to show its flexibility, performance, and correctness.

Denny, Joel↗
DOE OSTI2017

Structures and transitions in tungsten grain boundaries

The objective of this study is to develop a computational methodology to predict structure, energies of tungsten grain boundaries as a function of misorientation and inclination. The energies and the mobilities are the necessary input for thermomechanical model of recrystallization of tungsten for magnetic fusion applications being developed by the Marian Group at UCLA.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

In-plane g factor of low-density two-dimensional holes in a Ge quantum well.

High-mobility two-dimensional (2D) holes residing in a Ge quantum well are a new electronic system with potentials in quantum computing and spintronics. Since for any electronic material, the effective mass and the g factor are two fundamental material parameters that determine the material response to electric and magnetic fields, measuring these two parameters in this material system is thus an important task that needs to be completed urgently. Because of the quantum confinement in the crystal growth direction (z), the biaxial strain of epitaxial Ge on SiGe, and the valance band nature, both the effective mass and the g factor can show very strong anisotropy. In particular, the in-plane g factor (g ip ) can be vanishingly small while the perpendicular g factor (g z ) can be much larger than 2. Here we report the measurement of g ip at very low hole densities using in-plane magneto-resistance measurement performed at the NHMFL.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Emulating the Android Boot Process

Critical vulnerabilities continue to be discovered in the boot process of Android smartphones used around the world. The entire device's security is compromised if boot security is compromised, so any weakness presents undue risk to users. Vulnerabilities persist, in part, because independent security analysts lack access and appropriate tools. In response to this gap, we implemented a procedure for emulating the early phase of the Android boot process. This work demonstrated feasibility and utility of emulation in this space. By using HALucinator, we derived execution context and data flow, as well as incorporated peripheral hardware behavior. While smartphones with shared processors have substantial code overlap regardless of vendor, generational changes can have a significant impact. By applying our approach to older and modern devices, we learned interesting characteristics about the system. Such capabilities introduce new levels of introspection and operation understanding not previously available to mobile researchers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗
DOE OSTI2017

Symptoms and the use of wireless communication devices: A prospective cohort study in Swiss adolescents

Background: We investigated whether radiofrequency electromagnetic fields (RF-EMF) from mobile phones and other wireless devices or by the wireless device use itself due to non-radiation related factors in that context are associated with an increase in health symptom reports of adolescents in Central Switzerland. Methods: In a prospective cohort study, 439 study participants (participation rate: 36.8%) aged 12–17 years, completed questionnaires about their mobile and cordless phone use, their self-reported symptoms and possible confounding factors at baseline (2012/2013) and one year later (2013/2014). Operator recorded mobile phone data was obtained for a subgroup of 234 adolescents. RF-EMF dose measures considering various factors affecting RF-EMF exposure were computed for the brain and the whole body. Data were analysed using a mixed-logistic cross-sectional model and a cohort approach, where we investigated whether cumulative dose over one year was related to a new onset of a symptom between baseline and follow-up. All analyses were adjusted for relevant confounders. Results: Participation rate in the follow-up was 97% (425 participants). In both analyses, cross-sectional and cohort, various symptoms tended to be mostly associated with usage measures that are only marginally related to RF-EMF exposure such as the number of text messages sent per day (e.g. tiredness: OR:1.81; 95%CI:1.20–2.74 for cross-sectional analyses and OR:1.87; 95%CI:1.04–3.38 for cohort analyses). Outcomes were generally less strongly or not associated with mobile phone call duration and RF-EMF dose measures. Conclusions: Stronger associations between symptoms of ill health and wireless communication device use than for RF-EMF dose measures were observed. Such a result pattern does not support a causal association between RF-EMF exposure and health symptoms of adolescents but rather suggests that other aspects of extensive media use are related to symptoms. - Highlights: • This is a prospective cohort study with approximately one year of follow-up. • Self-reported and operator recorded mobile phone use data were collected. • The cumulative RF-EMF dose for the brain and for the whole body was calculated. • Associations were stronger for the use of wireless devices than for RF-EMF dose. • This suggests that rather aspects of extensive media use than RF-EMF are related to symptoms.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Revisiting matrix-based inversion of scanning mobility particle sizer (SMPS) and humidified tandem differential mobility analyzer (HTDMA) data

Abstract. Tikhonov regularization is a tool for reducing noise amplification during data inversion. This work introduces RegularizationTools.jl, a general-purpose software package for applying Tikhonov regularization to data. The package implements well-established numerical algorithms and is suitable for systems of up to ∼ 1000 equations. Included is an abstraction to systematically categorize specific inversion configurations and their associated hyperparameters. A generic interface translates arbitrary linear forward models defined by a computer function into the corresponding design matrix. This obviates the need to explicitly write out and discretize the Fredholm integral equation, thus facilitating fast prototyping of new regularization schemes associated with measurement techniques. Example applications include the inversion involving data from scanning mobility particle sizers (SMPSs) and humidified tandem differential mobility analyzers (HTDMAs). Inversion of SMPS size distributions reported in this work builds upon the freely available software DifferentialMobilityAnalyzers.jl. The speed of inversion is improved by a factor of ∼ 200, now requiring between 2 and 5 ms per SMPS scan when using 120 size bins. Previously reported occasional failure to converge to a valid solution is reduced by switching from the L-curve method to generalized cross-validation as the metric to search for the optimal regularization parameter. Higher-order inversions resulting in smooth, denoised reconstructions of size distributions are now included in DifferentialMobilityAnalyzers.jl. This work also demonstrates that an SMPS-style matrix-based inversion can be applied to find the growth factor frequency distribution from raw HTDMA data while also accounting for multiply charged particles. The outcome of the aerosol-related inversion methods is showcased by inverting multi-week SMPS and HTDMA datasets from ground-based observations, including SMPS data obtained at Bodega Marine Laboratory during the CalWater 2/ACAPEX campaign and co-located SMPS and HTDMA data collected at the US Department of Energy observatory located at the Southern Great Plains site in Oklahoma, USA. Results show that the proposed approaches are suitable for unsupervised, nonparametric inversion of large-scale datasets as well as inversion in real time during data acquisition on low-cost reduced-instruction-set architectures used in single-board computers. The included software implementation of Tikhonov regularization is freely available, general, and domain-independent and thus can be applied to many other inverse problems arising in atmospheric measurement techniques and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A fast platform for simulating semi-flexible fiber suspensions applied to cell mechanics

We present a novel platform for the large-scale simulation of three-dimensional fibrous structures immersed in a Stokesian fluid and evolving under confinement or in free-space in three dimensions. One of the main motivations for this work is to study the dynamics of fiber assemblies within biological cells. For this, we also incorporate the key biophysical elements that determine the dynamics of these assemblies, which include the polymerization and depolymerization kinetics of fibers, their interactions with molecular motors and other objects, their flexibility, and hydrodynamic coupling. This work, to our knowledge, is the first technique to include many-body hydrodynamic interactions (HIs), and the resulting fluid flows, in cellular assemblies of flexible fibers. We use non-local slender body theory to compute the fluid–structure interactions of the fibers and a second-kind boundary integral formulation for other rigid bodies and the confining boundary. A kernel-independent implementation of the fast multipole method is utilized for efficient evaluation of HIs. The deformation of the fibers is described by nonlinear Euler–Bernoulli beam theory and their polymerization is modeled by the reparametrization of the dynamic equations in the appropriate non-Lagrangian frame. We use a pseudo-spectral representation of fiber positions and implicit time-stepping to resolve large fiber deformations, and to allow time-steps not excessively constrained by temporal stiffness or fiber–fiber interactions. The entire computational scheme is parallelized, which enables simulating assemblies of thousands of fibers. We use our method to investigate two important questions in the mechanics of cell division: (i) the effect of confinement on the hydrodynamic mobility of microtubule asters; and (ii) the dynamics of the positioning of mitotic spindle in complex cell geometries. Finally to demonstrate the general applicability of the method, we simulate the sedimentation of a cloud of semi-flexible fibers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

MEP Metric Correlations with Socioeconomic and Built Environment Factors [Slides]

NREL's Mobility Energy Productivity tool, or MEP, quantifies the ability of an area's transportation system to connect individuals to goods, services, employment opportunities, and other activities while accounting for time, cost, and energy. However, the MEP tool itself does not examine correlations between mobility energy productivity and other sociodemographic and built environment variables relevant to the urban and transportation planning space. Examining these correlations could have two possible implications -- first, understanding what factors correlate with mobility energy productivity could help urban planners make equitable decisions in allocating transportation resources. Second, as the MEP has not been calculated for all urban areas in the US and is computationally expensive, if other publicly available variables were predictive enough of MEP then a simple model could be used to predict MEP instead of having to compute it for an area for which it has not been updated. A statistical analysis to investigate both of these questions is presented, with many significant associations found between the MEP and identified variables of interest.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Potential for high thermoelectric performance in n-type Zintl compounds: A case study of Ba doped KAlSb 4

High-throughput calculations (first-principles density functional theory and semi-empirical transport models) have the potential to guide the discovery of new thermoelectric materials. Herein we have computationally assessed the potential for thermoelectric performance of 145 complex Zintl pnictides. Of the 145 Zintl compounds assessed, 17% show promising n-type transport properties, compared with only 6% showing promising p-type transport. We predict that n-type Zintl compounds should exhibit high mobility μ n while maintaining the low thermal conductivity κ L typical of Zintl phases. Thus, not only do candidate n-type Zintls outnumber their p-type counterparts, but they may also exhibit improved thermoelectric performance. From the computational search, we have selected n-type KAlSb 4 as a promising thermoelectric material. Synthesis and characterization of polycrystalline KAlSb 4 reveals non-degenerate n-type transport. With Ba substitution, the carrier concentration is tuned between 10 18 and 10 19 e – cm –3 with a maximum Ba solubility of 0.7% on the K site. High temperature transport measurements confirm a high μ n (50 cm 2 V –1 s –1 ) coupled with a near minimum κ L (0.5 W m –1 K –1 ) at 370 °C. Together, these properties yield a zT of 0.7 at 370 °C for the composition K 0.99 Ba 0.01 AlSb 4 . As a result, based on the theoretical predictions and subsequent experimental validation, we find significant motivation for the exploration of n-type thermoelectric performance in other Zintl pnictides.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Computational Investigation of Technetium(IV) Incorporation into Inverse Spinels: Magnetite (Fe 3 O 4 ) and Trevorite (NiFe 2 O 4 )

Iron oxides and oxyhydroxides play an important role in minimizing the mobility of redox-sensitive elements in engineered and natural environments. For the radionuclide technetium-99 (Tc), these phases hold promise as primary hosts for increasing Tc loading into glass waste form matrices, or as secondary sinks during the long-term storage of nuclear materials. Recent experiments show that the inverse spinel, magnetite [Fe(II)Fe(III)2O4], can incorporate Tc(IV) into its octahedral sub-lattice, and in that same class of materials, trevorite [Ni(II)Fe(III)2O4] is also being investigated for its ability to host Tc(IV). However, questions remain regarding the most energetically favorable charge-compensation mechanism for Tc(IV) incorporation in each structure, which will affect Tc behavior under changing waste processing or storage conditions. Here, quantum-mechanical methods were used to evaluate incorporation energies and optimized lattice bonding environments for three different, charge-balanced Tc(IV) incorporation mechanisms in magnetite and trevorite. In both cases, the removal of two octahedral Fe(II) or Ni(II) ions upon the addition of Tc(IV) to an octahedral site is the most stable mechanism, relative to the creation of octahedral Fe(III) defects or increasing octahedral Fe(II) content. Following hydration-energy corrections, Tc(IV) incorporation into magnetite is energetically favorable while an energy barrier exists for trevorite.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2022

Symmetry-Breaking and Self-Sorting in Block Copolymer-Based Multicomponent Nanocomposites

Co-assembly of inorganic nanoparticles (NPs) and nanostructured polymer matrix represents an intricate interplay of enthalpic or entropic forces. Particle size largely affects the phase behavior of the nanocomposite. Theoretical studies indicate that new morphologies would emerge when the particles become comparable to the soft matrix's size, but this has rarely been supported experimentally. By designing a multicomponent blend composed of NPs, block copolymer-based supramolecules, and small molecules, a 3-D ordered lattice beyond the native BCP's morphology was recently reported when the particle is larger than the microdomain of BCP. The blend can accommodate various formulation variables. In this work, when the particle size equals the microdomain size, a symmetry-broken phase appears in a narrow range of particle sizes and compositions, which we named the "train track" structure. In this phase, the NPs aligned into a 3-D hexagonal lattice and packed asymmetrically along the c axis, making the projection of the ac and the bc plane resemble train tracks. Computational studies show that the broken symmetry reduces the polymer chain deformation and stabilizes the metastable hexagonally perforated lamellar morphology. Given the mobility of the multicomponent blend, the system shows a self-sorting behavior: segregating into two macroscopic phases with different nanostructures based on only a few nanometers NP size differences. Smaller NPs form "train track" morphology, while larger NPs form a "simple hexagon" structure, where the NPs take a symmetric hexagonal arrangement. Detailed structural evolution and simulation studies confirm the systematic-wide cooperativity across different components, indicating the strong self-regulation of the multicomponent system.

"train track" morphology↗
DOE OSTI2020

Changes in short- and medium-range order in metallic liquids during undercooling

It has been widely speculated that dominant motifs, such as short-range icosahedral order, can influence glass formation and the properties of glasses. Experimental data on both fragile and strong undercooled liquids demonstrate corresponding changes in their thermophysical properties consistent with increasing development of a network of interconnect motifs based on molecular dynamics. Describing these regions of local order, how they connect, and how they are related to property changes have been challenging issues, both computationally and experimentally. Yet the consensus is that metallic liquids develop interconnected medium-range order consisting of some regions with lower mobility with deeper undercooling. Less well understood is how these motifs (or “crystal genes”) in the liquid can inhibit nucleation in the deeply undercooled liquid or influence phase selection upon devitrification. These motifs tend to have local packing unlike stable compounds with icosahedral order tending to dominate the best glass formers. The underlying kinetic and thermodynamic forces that guide the formation of these motifs and how they interconnect during undercooling remain open questions.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Multilevel Semantic Labeling of Mobile Homes from Overhead Imagery

Finding where people live and the vulnerabilities of man-made facilities during natural disasters, is not only critical for rescue efforts, but also essential for damage assessment in the aftermath. Leveraging on the availability of high resolution satellite imagery, advances in machine learning and high performance computing hardware, it is now possible to generate geographical maps for man-made facilities at scale. Mapping from satellite imagery can be a daunting task due to the enormous amount of data to be processed over large areas. In this short paper we take advantage of annotated satellite imagery and automate the semantic labeling of mobile home parks using an efficient framework rooted in patch-based and pixel-level classification. This multilevel labeling effort is a precursor to our future goal for deploying very large scale deep convolutional neural networks toward both broad and finer characterization of man-made structures from one-meter resolution NAIP images.

Lunga, Dalton↗
DOE OSTI2022

Modeling receptor flexibility in the structure-based design of KRAS G12C inhibitors

KRAS has long been referred to as an ‘undruggable’ target due to its high affinity for its cognate ligands (GDP and GTP) and its lack of readily exploited allosteric binding pockets. Recent progress in the development of covalent inhibitors of KRAS G12C has revealed that occupancy of an allosteric binding site located between the α3-helix and switch-II loop of KRAS G12C —sometimes referred to as the ‘switch-II pocket’—holds great potential in the design of direct inhibitors of KRAS G12C . In studying diverse switch-II pocket binders during the development of sotorasib (AMG 510), the first FDA-approved inhibitor of KRAS G12C , we found the dramatic conformational flexibility of the switch-II pocket posing significant challenges toward the structure-based design of inhibitors. Here, we present our computational approaches for dealing with receptor flexibility in the prediction of ligand binding pose and binding affinity. For binding pose prediction, we modified the covalent docking program CovDock to allow for protein conformational mobility. This new docking approach, termed as FlexCovDock, improves success rates from 55 to 89% for binding pose prediction on a dataset of 10 cross-docking cases and has been prospectively validated across diverse ligand chemotypes. For binding affinity prediction, we found standard free energy perturbation (FEP) methods could not adequately handle the significant conformational change of the switch-II loop. We developed a new computational strategy to accelerate conformational transitions through the use of targeted protein mutations. Using this methodology, the mean unsigned error (MUE) of binding affinity prediction were reduced from 1.44 to 0.89 kcal/mol on a set of 14 compounds. These approaches were of significant use in facilitating the structure-based design of KRAS G12C inhibitors and are anticipated to be of further use in the design of covalent (and noncovalent) inhibitors of other conformationally labile protein targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Non-dilute helium-related defect interactions in the near-surface region of plasma-exposed tungsten

We report a systematic energetic analysis of helium-related defect interactions that mediate helium (He) segregation on surfaces of plasma-exposed tungsten at different levels of He ion implantation. We focus on high He fluences that increase the He content in the plasma-exposed material well beyond the dilute limit of He concentration and employ atomic configurations generated by large-scale molecular dynamics simulations of He-implanted tungsten. We perform systematic molecular statics computations of cluster– defect interaction energetics in the highly defect-rich near-surface region of plasma-exposed tungsten for small mobile helium clusters as a function of the cluster distance from the surface. In this region, mobile clusters are also subjected to the stress fields generated by defects such as helium bubbles and other clusters, which govern cluster–defect interactions in addition to the cluster–surface interaction. Based on systematic investigation of individual cluster–defect interactions, we develop a mathematical framework to describe the interaction energy landscapes consisting of elastic interaction potential perturbations to finite-width square-well potentials, where the potential well accounts for cluster trapping by the defect at close range and subsequent coalescence and the perturbation potential is parameterized according to elastic inclusion theory. Superposition of all the relevant interaction potentials provides a comprehensive description of the interaction energy landscape that would be experienced by a small mobile cluster along its migration path toward the plasma-exposed surface at high He fluence. Such descriptions are particularly important for developing atomistically-informed, hierarchical multi-scale models of helium cluster dynamics in plasma-facing materials.

36 MATERIALS SCIENCE↗