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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrated Spatial, Spectral, & Temporal Optical Reflectance System for Precision Occupancy & Location Sensing to Improve Building Energy Efficiency

Buildings consume approximately 35% of the electricity used in the U.S. and building owners can significantly reduce this energy use by providing services like heating, electrical power and lighting only when people are present. The ARPAe funded program titled “INTEGRATED SPATIAL, SPECTRAL, & TEMPORAL OPTICAL REFLECTANCE SYSTEM FOR PRECISION OCCUPANCY & LOCATION SENSING TO IMPROVE BUILDING ENERGY EFFICIENCY” demonstrates how a low cost sensor technology developed for measuring distances can be used to count and locate occupants with a high degree of precision with a very low error rates. This platform tells a building control system where occupants are located (but not who they are) so that energy consuming services can be provided only when the services are needed by building occupants. The original proof of concept involved using low cost, commercially available time-of-flight (TOF) sensors that measure distance, but the performance of these existing sensors was lacking, as they could not operate properly in the presence of sunlight, which blinded the simple TOF sensors and limited their utility in buildings. This project proposed a powerful new class of TOF sensors that used state-of-the-art integrated circuit (IC) fabrication processes that combined advanced photonics with conventional silicon chip circuitry for improved sensor performance. An equally important part of this project was to find ways to maximize occupant count and location accuracy while using the fewest number of sensors possible, in order to keep costs low. By using building blueprints to create digital twins of commercial building spaces, the team developed new algorithms to maximize occupant count and tracking accuracy by properly locating the minimum number of sensors at just the right spots in the building. This capability not only minimizes system costs but also simplified sensor installation and system commissioning. Our simulations of our sensor networks for a range of commercial floorplan designs demonstrated that our installed cost target of $0.08/sqft was attainable, though not fully demonstrated during the project. Finally, we noted that the TOF sensor concept could provide a valuable role in health and eldercare by tracking patients without the need for worn sensors and would be useful for fall detection and other patient safety metrics, including tracking healthcare/patient interactions. We feel that, when fully developed, this new class of sophisticated TOF sensors and support software will be a powerful new approach to improving building energy efficiency based on occupant centric control platforms and will also open new levels of patient safety in healthcare operations. To realize this potential, the team formed the Troy Sensor Company LLC to oversee licensing of the programs patents and continue to seek commercialization of this program’s activity sensing technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

DARK MATTER SEARCHES IN THE GAMMA-RAY EXTRAGALACTIC BACKGROUND VIA CROSS-CORRELATIONS WITH GALAXY CATALOGS

We compare the measured angular cross-correlation between the Fermi-Large Area Telescope γ-ray sky and catalogs of extragalactic objects with the expected signal induced by weakly interacting massive particle (WIMP) dark matter (DM). We include a detailed description of the contribution of astrophysical γ-ray emitters such as blazars, misaligned active galactic nucleus (AGN), and star-forming galaxies, and perform a global fit to the measured cross-correlation. Five catalogs are considered: Sloan Digital Sky Survey (SDSS)-DR6 quasars, Two Micron All Sky Survey galaxies, NRAO VLA Sky Survey radio galaxies, SDSS-DR8 Luminous Red Galaxies, and the SDSS-DR8 main galaxy sample. To model the cross-correlation signal, we use the halo occupation distribution formalism to estimate the number of galaxies of a given catalog in DM halos and their spatial correlation properties. We discuss uncertainties in the predicted cross-correlation signal arising from the DM clustering and WIMP microscopic properties, which set the DM γ-ray emission. The use of different catalogs probing objects at different redshifts significantly reduces, though not completely, the degeneracy among the different γ-ray components. We find that the presence of a significant WIMP DM signal is allowed by the data but not significantly preferred by the fit, although this is mainly due to a degeneracy with the misaligned AGN component. With modest substructure boost, the sensitivity of this method excludes thermal annihilation cross sections at 95% level for WIMP masses up to few tens of GeV. Constraining the low-redshift properties of astrophysical populations with future data will further improve the sensitivity to DM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Connective Actions for Educational Institutions and Wind Industry Firms [Slides]

As a part of the National Wind Workforce Assessment, four presentations have been created in conjunction with the technical report to provide more insight into key findings. The four presentations are catered towards specific stakeholder groups that include: educators, wind industry firms, students, and current wind industry employees. This presentation is intended for use by wind industry firms and educational institutions looking to gain insight into key levers and actionable steps that can be taken to help narrow the wind workforce gap. Data and guidance on how wind industry firms and education institutions can collaborate to 1) grow the number of graduates applying into wind occupational roles through increasing awareness of opportunities in the industry and 2) increase the quality of applicants applying into wind through relevant experience gaining opportunities like internships and apprenticeships is included in the presentation.

17 WIND ENERGY↗
DOE OSTI2013

Efficient Aho-Corasick String Matching on Emerging Multicore Architectures

String matching algorithms are critical to several scientific fields. Beside text processing and databases, emerging applications such as DNA protein sequence analysis, data mining, information security software, antivirus, ma- chine learning, all exploit string matching algorithms [3]. All these applica- tions usually process large quantity of textual data, require high performance and/or predictable execution times. Among all the string matching algorithms, one of the most studied, especially for text processing and security applica- tions, is the Aho-Corasick algorithm. 1 2 Book title goes here Aho-Corasick is an exact, multi-pattern string matching algorithm which performs the search in a time linearly proportional to the length of the input text independently from pattern set size. However, depending on the imple- mentation, when the number of patterns increase, the memory occupation may raise drastically. In turn, this can lead to significant variability in the performance, due to the memory access times and the caching effects. This is a significant concern for many mission critical applications and modern high performance architectures. For example, security applications such as Network Intrusion Detection Systems (NIDS), must be able to scan network traffic against very large dictionaries in real time. Modern Ethernet links reach up to 10 Gbps, and malicious threats are already well over 1 million, and expo- nentially growing [28]. When performing the search, a NIDS should not slow down the network, or let network packets pass unchecked. Nevertheless, on the current state-of-the-art cache based processors, there may be a large per- formance variability when dealing with big dictionaries and inputs that have different frequencies of matching patterns. In particular, when few patterns are matched and they are all in the cache, the procedure is fast. Instead, when they are not in the cache, often because many patterns are matched and the caches are continuously thrashed, they should be retrieved from the system memory and the procedure is slowed down by the increased latency. Efficient implementations of string matching algorithms have been the fo- cus of several works, targeting Field Programmable Gate Arrays [4, 25, 15, 5], highly multi-threaded solutions like the Cray XMT [34], multicore proces- sors [19] or heterogeneous processors like the Cell Broadband Engine [35, 22]. Recently, several researchers have also started to investigate the use Graphic Processing Units (GPUs) for string matching algorithms in security applica- tions [20, 10, 32, 33]. Most of these approaches mainly focus on reaching high peak performance, or try to optimize the memory occupation, rather than looking at performance stability. However, hardware solutions supports only small dictionary sizes due to lack of memory and are difficult to customize, while platforms such as the Cell/B.E. are very complex to program.

Tumeo, Antonino↗
DOE OSTI2013

Accounting for Incomplete Species Detection in Fish Community Monitoring

Riverine fish assemblages are heterogeneous and very difficult to characterize with a one-size-fits-all approach to sampling. Furthermore, detecting changes in fish assemblages over time requires accounting for variation in sampling designs. We present a modeling approach that permits heterogeneous sampling by accounting for site and sampling covariates (including method) in a model-based framework for estimation (versus a sampling-based framework). We snorkeled during three surveys and electrofished during a single survey in suite of delineated habitats stratified by reach types. We developed single-species occupancy models to determine covariates influencing patch occupancy and species detection probabilities whereas community occupancy models estimated species richness in light of incomplete detections. For most species, information-theoretic criteria showed higher support for models that included patch size and reach as covariates of occupancy. In addition, models including patch size and sampling method as covariates of detection probabilities also had higher support. Detection probability estimates for snorkeling surveys were higher for larger non-benthic species whereas electrofishing was more effective at detecting smaller benthic species. The number of sites and sampling occasions required to accurately estimate occupancy varied among fish species. For rare benthic species, our results suggested that higher number of occasions, and especially the addition of electrofishing, may be required to improve detection probabilities and obtain accurate occupancy estimates. Community models suggested that richness was 41% higher than the number of species actually observed and the addition of an electrofishing survey increased estimated richness by 13%. These results can be useful to future fish assemblage monitoring efforts by informing sampling designs, such as site selection (e.g. stratifying based on patch size) and determining effort required (e.g. number of sites versus occasions).

fish sampling↗
DOE OSTI2021

Decoding ionic conductivity and reordering in cation-disordered pyrochlores

The ordered structure A 2 B 2 O 6 O’ in pyrochlores engenders twin rows of inequivalent anion sublattices each centred on alternating cations. While it is known that cation antisite disorder augments the ionic conductivity by several orders of magnitude, the local cation environment around the anions and the dynamic anion reordering during the cation disordering are not well-elucidated. Using atomistic simulations on Gd 2 Zr 2 O 7 , we first show that the anions engage in concerted hops to the neighbouring tetrahedral sites mostly along with the $\langle$1 0 0$\rangle$ direction while completely avoiding the octahedral sites. While the initially vacant 8 a sites start accommodating oxygen ions with increasing cation disorder, they show noticeable reluctance even at significant levels of disorder. We have also tracked both the distribution of available oxygen sites following random cation disorder, which is dependent only on cation disordering, and the probability of occupation of these sites. Interestingly, the available oxygen sites show a non-monotonic dependence on the number of B ions in the nearest neighbouring shell while the occupation probability of all the available oxygen sites increases monotonically. A tetrahedral oxygen site thus has a better probability of being occupied when it has a greater number of second neighbour B ions. This article is part of the Theo Murphy meeting issue 'Understanding fast-ion conduction in solid electrolytes'.

Science & Technology - Other Topics↗
DOE OSTI2014

Analysis of proton single-particle properties of zinc and germanium isotopes

Experimental proton single-particle energies in the vicinity of the Fermi energy for stable zinc and germanium isotopes are analyzed on the basis the dispersive optical model. The values found for the parameters of the dispersive optical potential are corrected with the aim of matching the total number of protons that is calculated with the aid of the function of Bardeen-Cooper-Schrieffer theory for the occupation probability for single-particle orbits with the charge number Z of the nucleus. The parameters of the dispersive optical potential are extrapolated on the basis of physically motivated arguments to the region of unstable isotopes in which the number N ranges between 34 and 50, and single-particle spectra are predicted by means of calculations with these parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Thermodynamic stability of elemental boron allotropes with varying numbers of interstitial atoms

Elemental boron exists in multiple allotropes, each characterized by structures containing icosahedral subunits. These structures have interstitial sites between the icosahedral subunits that are partially occupied. The number of atoms in the unit cell varies depending on the occupancy of these interstitial sites. Here we have investigated the thermodynamic stability of boron allotropes for different numbers of atoms in the unit cell by calculating the free energies, including the contribution of phonons. It has been found that β-rhombohedral boron is most stable with 107 atoms/cell at low temperatures, while it becomes most stable with 105 atoms/cell above 1700 K. This suggests the occurrence of a phase transition at this temperature, which could account for the large variation in the number of atoms in the unit cell for β-rhombohedral boron samples. α-tetragonal boron is consistently most stable with 52 atom/cell and becomes unstable with more than 52 atoms/cell. Similar to β-rhombohedral boron, β-tetragonal boron may undergo a phase transition between 192 and 190 atoms/cell configurations. However, the thermodynamic stability of pure β-tetragonal boron has been questioned in comparison with other allotropes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Impacts of satellite galaxies on the redshift-space distortions

We study the impacts of the satellite galaxies on the redshift-space distortions. In our multipole power spectrum analysis of the luminous red galaxies (LRGs) samples of the Sloan digital sky survey (SDSS), we have clearly detected the non-zero signature of the hexadecapole and tetrahexadecapole spectrum, which almost disappears in the power spectrum with the sample of the brightest LRGs only. We thus demonstrate that the satellite LRGs in multiple systems make a significant contribution to the multipole power spectrum though its fraction is small. The behavior can be understood by a simple halo model, in which the one-halo term, describing the Finger of God (FoG) effect from the satellite galaxies, makes the dominant contribution to the higher multipole spectra. We demonstrate that the small-scale information of higher multipole spectrum is useful for calibrating the satellite FoG effect and improves the measurement of the cosmic growth rate dramatically. We further demonstrate that the fiber collision in the galaxy survey influences the one-halo term and the higher multipole spectra, because the number of satellite galaxies in the halo occupation distribution (HOD) is changed. We also discuss about the impact of satellite galaxies on future high-redshift surveys targeting the H-alpha emitters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Hybrid gausslet/Gaussian basis sets

We introduce hybrid gausslet/Gaussian basis sets, where a standard Gaussian basis is added to a gausslet basis in order to increase accuracy near the nuclei while keeping the spacing of the grid of gausslets relatively large. The Gaussians are orthogonalized to the gausslets, which are already orthonormal, and approximations are introduced to maintain the diagonal property of the two electron part of the Hamiltonian so that it continues to scale as the second power of the number of basis functions rather than the fourth. We introduce several corrections to the Hamiltonian designed to enforce certain exact properties, such as the values of certain two-electron integrals. We also introduce a simple universal energy correction that compensates for the incompleteness of the basis stemming from the electron–electron cusps based on the measured double occupancy of each basis function. We perform a number of Hartree Fock and full configuration interaction (full-CI) test calculations on two electron systems and Hartree Fock on a ten-atom hydrogen chain to benchmark these techniques. The inclusion of the cusp correction allows us to obtain complete basis set full-CI results for the two electron cases at the level of several micro-Hartrees, and we see similar apparent accuracy for Hartree Fock on the ten-atom hydrogen chain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Biokinetic data and models for occupational intake of lanthanoids

The lanthanoid (or lanthanide) chemical elements comprise fifteen elements with atomic numbers 57 (lanthanum) through 71 (lutetium). This paper reviews data related to the biological behavior of these elements in the human body and proposes biokinetic models for application to occupational intake of radio-lanthanoids. Generic (element-independent) absorption rates from the respiratory and alimentary tracts to blood are proposed. The proposed systemic models are largely generic but include some element-specific parameter values to reflect regular changes with ionic radius in certain aspects of the behavior of the lanthanoids. This work was performed within the internal dosimetry task group (INDOS) of Committee 2 of the International Commission on Radiological Protection (ICRP).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Flows of engineered nanomaterials through the recycling process in Switzerland

Highlights: • Recycling is one of the likely end-of-life fates of nanoproducts. • We assessed the material flows of four nanomaterials in the Swiss recycling system. • After recycling, most nanomaterials will flow to landfills or incineration plants. • Recycled construction waste, plastics and textiles may contain nanomaterials. - Abstract: The use of engineered nanomaterials (ENMs) in diverse applications has increased during the last years and this will likely continue in the near future. As the number of applications increase, more and more waste with nanomaterials will be generated. A portion of this waste will enter the recycling system, for example, in electronic products, textiles and construction materials. The fate of these materials during and after the waste management and recycling operations is poorly understood. The aim of this work is to model the flows of nano-TiO{sub 2}, nano-ZnO, nano-Ag and CNT in the recycling system in Switzerland. The basis for this study is published information on the ENMs flows on the Swiss system. We developed a method to assess their flow after recycling. To incorporate the uncertainties inherent to the limited information available, we applied a probabilistic material flow analysis approach. The results show that the recycling processes does not result in significant further propagation of nanomaterials into new products. Instead, the largest proportion will flow as waste that can subsequently be properly handled in incineration plants or landfills. Smaller fractions of ENMs will be eliminated or end up in materials that are sent abroad to undergo further recovery processes. Only a reduced amount of ENMs will flow back to the productive process of the economy in a limited number of sectors. Overall, the results suggest that risk assessment during recycling should focus on occupational exposure, release of ENMs in landfills and incineration plants, and toxicity assessment in a small number of recycled inputs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Impact of microkinetic modeling assumptions on predicted kinetics and mechanisms over undercoordinated sites

Accurate modeling of catalytic reactions on undercoordinated sites requires accounting for the structural and ensemble-specific nature of the active sites. This study examines how common microkinetic modeling (MKM) assumptions affect predicted kinetics and mechanisms on the stepped Pt(211) facet for the ethane dehydrogenation (EDH) and the ethane hydrogenolysis (EH). Six (211) MKMs were developed, differing in (i) the number of active sites represented, (ii) adsorbate site occupancy treatment, and (iii) inclusion of cross-facet interactions. These models are benchmarked against a particle-based microkinetic model (PB-MKM), which best represents step-edge behavior. MKM assumptions caused deviations in turnover frequencies exceeding ten orders of magnitude and led to contrasting mechanistic and selectivity predictions. Multi-site MKMs overestimate activity by inflating free site availability, single-site models underestimate activity, and uniform occupancy models overpredict coverage of multi-dentate intermediates, leading to reaction-specific artifacts. Overall, the Combined Site Edge Model (CSEM), a single-site MKM accounting for site occupancy and cross-facet interactions, most closely approximates PB-MKM predictions. All models predict similar kinetics when surfaces are clean or primarily occupied by monodentate species. This work provides practical guidance for selecting MKM frameworks for undercoordinated catalytic surfaces and highlights the critical role of modeling assumptions in catalytic predictions.

(211) facet↗
DOE OSTI2025

Readout electronics for low occupancy High-Pressure Gas TPCs

High-Pressure Gas Time Projection Chambers (HPgTPCs) have benefits such as low energy thresholds, magnetisability, and 4π acceptance, making them ideal for neutrino experiments such as DUNE. We present the design of an FPGA-based solution optimised for Gaseous Argon Near Detector (ND-GAr), which is part of the Phase-II more capable near detector for DUNE. These electronics reduce the cost significantly compared to using collider readout electronics, which are typically designed for much higher occupancy and therefore, for example, need much larger numbers of FPGAs and power per channel. We demonstrate the performance of our electronics with the Teststand for an Overpressurised Argon Detector (TOAD) at Fermilab in the US at a range of pressures and gas mixtures up to 4.5 barA, reading out ∼10 000 channels from a Multi-Wire Proportional Chamber (MWPC). The operation took place between April and July of 2024. We measure the noise characteristics of the system to be sufficiently low, and we identify sources of noise that can be further mitigated in the next iteration. We also note that the cooling scheme used in the test requires improvement before full-scale deployment. Despite these necessary improvements, we show that the system can fulfil the needs of a HPgTPC for a fraction of the price of collider readout electronics.

Data acquisition concepts↗
DOE OSTI2020

The Mertens Unrolled Network (MU-Net): A High Dynamic Range Fusion Neural Network for Through the Windshield Driver Recognition

Face recognition of vehicle occupants through windshields in unconstrained environments poses a number of unique challenges ranging from glare, poor illumination, driver pose and motion blur. In this paper, we further develop the hardware and software components of a custom vehicle imaging system to better overcome these challenges. After the build out of a physical prototype system that performs High Dynamic Range (HDR) imaging, we collect a small dataset of through-windshield image captures of known drivers. We then reformulate the classical Mertens-Kautz-Van Reeth HDR fusion algorithm as a pre-initialized neural network, which we name the Mertens Unrolled Network (MU-Net), for the purpose of fine-tuning the HDR output of through-windshield images. Reconstructed faces from this novel HDR method are then evaluated and compared against other traditional and experimental HDR methods in a pre-trained state-of-the-art (SOTA) facial recognition pipeline, verifying the efficacy of our approach.

Ruby, Max↗
DOE OSTI2016

Li-ion site disorder driven superionic conductivity in solid electrolytes: a first-principles investigation of β-Li 3 PS 4

The attractive safety and long-term stability of all solid-state batteries has added a new impetus to the discovery and development of solid electrolytes for lithium batteries. Recently several superionic lithium conducting solid electrolytes have been discovered. All the superionic lithium containing compounds (β-Li 3 PS 4 and Li 10 GeP 2 S 12 and oxides, predominantly in the garnet phase) have partially occupied sites. This naturally begs the question of understanding the role of partial site occupancies (or site disorder) in optimizing ionic conductivity in these family of solids. In this paper, we find that for a given topology of the host lattice, maximizing the number of sites with similar Li-ion adsorption energies, which gives partial site occupancy, is a natural way to increase the configurational entropy of the system and optimize the conductivity. For a given topology and density of Li-ion adsorption sites, the ionic conductivity is maximal when the number of mobile Li-ions are equal to the number of mobile vacancies, also the very condition for achieving maximal configurational entropy. We demonstrate applicability of this principle by elucidating the role of Li-ion site disorder and the local chemical environment in the high ionic conductivity of β-Li 3 PS 4 . In addition, for β-Li 3 PS 4 we find that a significant density of vacancies in the Li-ion sub-lattice (~25%) leads to sub-lattice melting at (~600 K) leading to a molten form for the Li-ions in an otherwise solid anionic host. This gives a lithium site occupancy that is similar to what is measured experimentally. We further show that quenching this disorder can improve conductivity at lower temperatures. As a consequence, we discover that (a) one can optimize ionic conductivity in a given topology by choosing a chemistry/composition that maximizes the number of mobile-carriers i.e. maximizing both mobile Li-ions and vacancies, and (b) when the concentration of vacancies becomes significant in the Li-ion sub-lattice, it becomes energetically as well as entropically favorable for it to remain molten well below the bulk decomposition temperature of the solid. Finally, this principle may already apply to several known superionic conducting solids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Fractal Dimension Calculation for Big Data Using Box Locality Index

The box-counting approach for fractal dimension calculation is scaled up for big data using a data structure named box locality index (BLI). The BLI is constructed as key-value pair style with the key (an integer array) indexing the location of a “box” (i.e., a gird cell on the multi-dimensional space embedding a given dataset) and the value counting the number of data points inside the box (called “box occupancy”). Compared with the traditionally used E-dim tree, the BLI avoids complex hierarchical structure and encodes only necessary information required by box-counting approach for fractal dimension calculation. Moreover, the key-value pair nature of BLI, together with the fact that the box occupancy is aggregatable, grants box-counting approach the needed scalability for fractal dimension calculation of big data using distributed computing techniques (e.g., MapReduce and Spark). Taking the advantage of the BLI, MapReduce and Spark methods for fractal dimension calculation of big data are developed, which conduct box-counting for each grid level as a cascade of MapReduce/Spark jobs in a bottom-up fashion. In an empirical validation, the MapReduce and Spark methods demonstrated good effectiveness and efficiency in fractal calculation of a big synthetic dataset. In summary, this work provides an efficient solution for the estimation of intrinsic dimension of big data that is essential for many machine learning methods and data analytics.

Fractal dimension, Intrinsic dimension, Box-counti↗