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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical‐based models to fully utilize the high‐resolution data under the constraints of computing resources. The advancement in machine learning (ML) techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a modeling framework that uses ML approach to estimate point‐scale street‐level air temperature from the urban‐resolving meso‐scale climate model and a suite of hyper‐resolution urban geospatial data sets, including three‐dimensional urban morphology, parcel‐level land use inventory, and weather observations from a sensor network. We implemented this approach in the City of Chicago as a case study to demonstrate the capability of the framework. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat‐related behavioral studies. Moreover, we tested the model's reliability on out‐of‐sample locations to investigate the modeling uncertainties and the application potentials to the other areas. This study aims to gain insights into next‐gen urban climate modeling and guide the observation efforts in cities to build the strength for the holistic understanding of urban microclimate dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Stormwater Storage and Retention Within an Urban Prairie Wetland Complex

Climate change is expected to increase the frequency and severity of flooding in the Great Lakes region. In many cities, flood-control infrastructure is insufficient to protect against future climate conditions. Consequently, there is increasing focus on stormwater storage provided by urban greenspace, such as wetlands and prairies, but the ecohydrological behavior of these ecosystems is not well understood when they are embedded within cities. To improve understanding of hydrological connectivity between urban areas and natural greenspaces, we deployed a sensor network in Gensburg Markham Prairie (GMP), a large intact prairie-wetland complex in south suburban Chicago. We used the resulting high-frequency time-series data to assess surface-subsurface hydrologic dynamics between upland and low-lying wetland areas, interactions between the prairie and surrounding environment, and stormwater storage provided by the prairie. Rapid infiltration within the prairie during and after storm events provides subsurface flow that stores considerable water, flattens storm hydrographs, and increases the wetland hydroperiod. Much of the stormwater input to GMP derives from the surrounding cityscape. Consequently, storage within the prairie-wetland system reduces and slows stormwater discharge to downstream urban communities. For a typical 5-year 24-hr storm with 10.9 cm of rain, GMP stores 77,100 m 3 , 64% greater than the estimated direct rainfall volume onto the prairie, yielding 30,000 m 3 of offsite stormwater storage. This improved understanding of ecohydrological dynamics in urban prairies and wetlands informs the design and implementation of green infrastructure to meet growing needs for stormwater management.

Rivera, Vivien Anne [Northwestern University, Evan↗
DOE OSTI2022

High-performance piezoelectric composites via β phase programming

Polymer-ceramic piezoelectric composites, combining high piezoelectricity and mechanical flexibility, have attracted increasing interest in both academia and industry. However, their piezoelectric activity is largely limited by intrinsically low crystallinity and weak spontaneous polarization. Here, we propose a Ti 3 C 2 T x MXene anchoring method to manipulate the intermolecular interactions within the all-trans conformation of a polymer matrix. Employing phase-field simulation and molecular dynamics calculations, we show that OH surface terminations on the Ti 3 C 2 T x nanosheets offer hydrogen bonding with the fluoropolymer matrix, leading to dipole alignment and enhanced net spontaneous polarization of the polymer-ceramic composites. We then translated this interfacial bonding strategy into electrospinning to boost the piezoelectric response of samarium doped Pb (Mg1/3Nb 2/3 )O 3 -PbTiO 3 /polyvinylidene fluoride composite nanofibers by 160% via Ti 3 C 2 T x nanosheets inclusion. With excellent piezoelectric and mechanical attributes, the as-electrospun piezoelectric nanofibers can be easily integrated into the conventional shoe insoles to form a foot sensor network for all-around gait patterns monitoring, walking habits identification and Metatarsalgi prognosis. This work utilizes the interfacial coupling mechanism of intermolecular anchoring as a strategy to develop high-performance piezoelectric composites for wearable electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Global evidence for the acclimation of ecosystem photosynthesis to light

Photosynthesis responds quickly to changes in light, increasing with incoming photosynthetic photon flux density (PPFD) until the leaves become light saturated. This instantaneous response to PPFD, which is widely studied and incorporated into models of photosynthesis, is overlaid on non-instantaneous photosynthetic changes resulting from the acclimation of plants to average PPFD over intermediate timescales of a week to months ($\overline{PPFD}$). Such photosynthetic light acclimation is not typically incorporated into models, due to the lack of observational constraints. In this work, we use eddy covariance observations from globally distributed and automated sensor networks, along with photosynthesis estimates from nine terrestrial biosphere models (TBMs), to quantify and assess photosynthetic acclimation to light in natural environments. We also use recent theoretical developments to incorporate light acclimation in a TBM. Our results show widespread light acclimation of ecosystem photosynthesis. On average, a 1 μmol m -2 s -1 increase in $\overline{PPFD}_{10}$ (ten-day average PPFD) leads to a 0.031 ± 0.013 μmol C m -2 s -1 increase in the maximum photosynthetic assimilation rate (A max ), with croplands having stronger acclimation rates than grasslands and forests. Our analysis shows that the TBMs examined either neglect or substantially underestimate light acclimation. By updating a TBM to include photosynthetic acclimation, successfully reproducing the $\overline{PPFD}_{10}$-A max relationship, we provide a robust method for the incorporation of photosynthetic light acclimation in future models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

High-speed programmable photonic circuits in a cryogenically compatible, visible–near-infrared 200 mm CMOS architecture

Abstract Recent advances in photonic integrated circuits have enabled a new generation of programmable Mach–Zehnder meshes (MZMs) realized by using cascaded Mach–Zehnder interferometers capable of universal linear-optical transformations on N input/output optical modes. MZMs serve critical functions in photonic quantum information processing, quantum-enhanced sensor networks, machine learning and other applications. However, MZM implementations reported to date rely on thermo-optic phase shifters, which limit applications due to slow response times and high power consumption. Here we introduce a large-scale MZM platform made in a 200 mm complementary metal–oxide–semiconductor foundry, which uses aluminium nitride piezo-optomechanical actuators coupled to silicon nitride waveguides, enabling low-loss propagation with phase modulation at greater than 100 MHz in the visible–near-infrared wavelengths. Moreover, the vanishingly low hold-power consumption of the piezo-actuators enables these photonic integrated circuits to operate at cryogenic temperatures, paving the way for a fully integrated device architecture for a range of quantum applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Binder-free highly conductive graphene laminate for low cost printed radio frequency applications

In this paper, we demonstrate realization of printable radio frequency identification (RFID) antenna by low temperature processing of graphene ink. The required ultra-low resistance is achieved by rolling compression of binder-free graphene laminate. With compression, the conductivity of graphene laminate is increased by more than 50 times compared to that of as-deposited one. Graphene laminate with conductivity of 4.3 × 10{sup 4 }S/m and sheet resistance of 3.8 Ω/sq (with thickness of 6 μm) is presented. Moreover, the formation of graphene laminate from graphene ink reported here is simple and can be carried out in low temperature (100 °C), significantly reducing the fabrication costs. A dipole antenna based on the highly conductive graphene laminate is further patterned and printed on a normal paper to investigate its RF properties. The performance of the graphene laminate antenna is experimentally measured. The measurement results reveal that graphene laminate antenna can provide practically acceptable return loss, gain, bandwidth, and radiation patterns, making it ideal for low cost printed RF applications, such as RFID tags and wearable wireless sensor networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Mitigating the Threat of Nuclear-Weapon Proliferation via Nuclear-Submarine Programs

Brazil is building a nuclear-powered attack submarine, South Korea has in the past asserted its need for nuclear-powered attack submarines to deal with the threat of North Korean nuclear-armed submarine-launched ballistic missiles, and Iran has asserted more vaguely its need for naval nuclear propulsion. All three countries are non-weapon-state parties to the Nuclear Nonproliferation Treaty (NPT). Their interest in naval reactors brings with it two challenges to the NPT: 1) The safeguards “loophole” under which a country can withdraw nuclear materials from IAEA safeguards indefinitely for allowed “non-peaceful activities;” and 2) A justification for the acquisition of national uranium-enrichment facilities because the international suppliers of enrichment services have peaceful-use requirements. In fact, Brazil’s acquisition of enrichment was driven by its navy. It is argued, however, that nuclear-powered attack submarines have advantages over modern conventional attack submarines primarily in their ability to transit great distances at high speed whereas only a few countries have foreign military commitments requiring such capabilities. For defense of nearby waters against foreign navies, attack submarines are merely one component of a complex system of anti-submarine aircraft and surface vessels and underwater sensor networks. Conventional attack submarines are no less effective and much less costly than nuclear-powered attack submarines in this role.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Insights on seasonal solifluction processes in warm permafrost Arctic landscape using a dense monitoring approach across adjacent hillslopes

Solifluction processes in the Arctic are highly complex, introducing uncertainties in estimating current and future soil carbon storage and fluxes, and assessment of hillslope and infrastructure stability. This study aims to enhance our understanding of triggers and drivers of soil movement of permafrost-affected hillslopes in the Arctic. To achieve this, we established an extensive soil deformation and temperature sensor network, covering 48 locations across multiple hillslopes within a 1 km² watershed on the Seward Peninsula, AK. We report depth-resolved measurements down to 1.8 m depth for May to September 2022, a period conducive to soil movement due to deepening thaw layers and frequent rain events. Over this period, surface movements of up to 334 mm were recorded. In general, these movements occur close to the thawing front, and are initiated as thawing reaches depths of 0.4 to 0.75 m. The largest movements were observed at the top of the south-east facing slope, where soil temperatures are cold (mean annual soil temperatures averaging -1.13°C) and slopes are steeper than 15°. Our analysis highlights three primary factors influencing movements: slope angle, soil thermal conditions, and thaw depth. The latter two significantly impact the generation of pore water pressures at the thaw–freeze interface. Specifically, soil thermal conditions govern the liquid water content, while thaw depth influences both the height of the water column and, consequently, the pressure at the thawing front. These factors affect soil properties, such as cohesion and internal friction angle, which are crucial determinants of slope stability. This underscores the significance of a precise understanding of subsurface thermal conditions, including spatial and temporal variability in soil temperature and thaw depth, when assessing and predicting slope instabilities. Based on our observations, we developed a Factor of Safety proxy that consistently falls below the triggering threshold for all probes exhibiting displacements exceeding 50 mm. This study offers novel insights into patterns and triggers of hillslope movements in the Arctic and provides a venue to evaluate their impact on soil redistribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Output-weighted sampling for multi-armed bandits with extreme payoffs

We present a new type of acquisition function for online decision-making in multi-armed and contextual bandit problems with extreme payoffs. Specifically, we model the payoff function as a Gaussian process and formulate a novel type of upper confidence bound acquisition function that guides exploration towards the bandits that are deemed most relevant according to the variability of the observed rewards. This is achieved by computing a tractable likelihood ratio that quantifies the importance of the output relative to the inputs and essentially acts as an attention mechanism that promotes exploration of extreme rewards. Our formulation is supported by asymptotic zero-regret guarantees, and its performance is demonstrated across several synthetic benchmarks, as well as two realistic examples involving noisy sensor network data. Finally, we provide a JAX library for efficient bandit optimization using Gaussian processes.

Science & Technology - Other Topics↗
DOE OSTI2024

Essay: Quantum Sensing with Atomic, Molecular, and Optical Platforms for Fundamental Physics

Atomic, molecular, and optical (AMO) physics has been at the forefront of the development of quantum science while laying the foundation for modern technology. With the growing capabilities of quantum control of many atoms for engineered many-body states and quantum entanglement, a key question emerges: what critical impact will the second quantum revolution with ubiquitous applications of entanglement bring to bear on fundamental physics? In this Essay, we argue that a compelling long-term vision for fundamental physics and novel applications is to harness the rapid development of quantum information science to define and advance the frontiers of measurement physics, with strong potential for fundamental discoveries. As quantum technologies, such as fault-tolerant quantum computing and entangled quantum sensor networks, become much more advanced than today’s realization, we wonder what doors of basic science can these tools unlock. We anticipate that some of the most intriguing and challenging problems, such as quantum aspects of gravity, fundamental symmetries, or new physics beyond the minimal standard model, will be tackled at the emerging quantum measurement frontier. . Published by the American Physical Society 2024

Physics↗
DOE OSTI2022

DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs

Coarse-grained reconfigurable arrays (CGRAs) provide higher flexibility than application-specific integrated circuits (ASICs) and higher efficiency than fine-grained reconfigurable devices such as Field Programmable Gate Arrays (FPGAs). However, CGRAs are generally designed to support offloading of a single kernel. While their design, based on communicating functional units, appears to naturally suit data streaming applications composed of multiple cooperating kernels, current approaches only statically partition the resources across application kernels. However, emerging streaming applications at the edge (scientific instruments, sensor networks, network processing) perform much more than digital signal processing and often are data and input dependent. This leads to extremely variable kernel execution times, severely impacting the throughput of the entire pipeline if resources are only statically allocated. Therefore, in this paper, we propose DRIPS — a coarse-grained, dynamically, and partially reconfigurable array for data-dependent streaming applications. We present a unified compiler framework to facilitate the mapping of a given streaming application onto the DRIPS CGRA architecture. The experimental results show that DRIPS achieves an average throughput improvement of 1.46$\times$ across a set of representative applications over a statically partitioned solution. The additional area overhead to enable dynamic rebalancing consumes 16.34% of the entire area for a 5x5 CGRA prototype.

Tan, Cheng↗
DOE OSTI2021

Sheaves as a Framework for Understanding and Interpreting Model Fit

As data grows in size and complexity, finding frameworks which aid in interpretation and analysis has become critical. This is particularly true when data comes from complex systems where extensive structure is available, but must be drawn from peripheral sources. In this paper we argue that in such situations, sheaves can provide a natural framework to analyze how well a statistical model fits at the local level (that is, on subsets of related datapoints) vs the global level (on all the data). The sheaf-based approach that we propose is suitably general enough to be useful in a range of applications, from analyzing sensor networks to understanding the feature space of a deep learning model.

Kvinge, Henry J.↗
DOE OSTI2020

Cyber-Physical Smart Light Control System Integration with Smart Grid using Zigbee

This paper presents a hardware-in-the-loop cyber-physical system architecture design to monitor and control smart lights connected to the active distribution grid. The architecture uses Zigbee-based (IEEE 802.15.4) wireless sensor networks and publish-subscribe architecture to exchange monitoring and control signals between smart-light actuators (SLAs) and a smart-light central controller (SLCC). Each SLA integrated into a smart light consists of a Zigbee-based endpoint module to send and receive signals to and from the SLCC. The SLCC consists of a Zigbee-based coordinator module, which further exchanges the monitoring and control signals with the active distribution management system over the TCP/IP communication network. The monitoring signals from the SLAs include light status, brightness level, voltage, current, and power data, whereas, the control signals to the SLAs include light intensity, turn ON, turn OFF, standby, and default settings. We have used our existing hardware-in-the-loop (HIL) cyber-physical system (CPS) security SCADA testbed to process signals received from the SLCC and respond suitable control signals based on the smart light schedule requirements, system operation, and active distribution grid dynamic characteristics. We have integrated the proposed cyber-physical smart light control system (CPSLCS) testbed to our existing HIL CPS SCADA testbed. We use the integrated testbed to demonstrate the efficacy of the proposed algorithm by real-time performance and latency between the SLCC and SLAs. The experiments demonstrated significant results by 100% realtime performance and low latency while exchanging data between the SLCC and SLAs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Room temperature multiplexed gas sensing using chemical-sensitive 3.5-nm-thin silicon transistors

There is great interest in developing a low-power gas sensing technology that can sensitively and selectively quantify the chemical composition of a target atmosphere. Nanomaterials have emerged as extremely promising candidates for this technology due to their inherent low-dimensional nature and high surface-to-volume ratio. Among these, nanoscale silicon is of great interest because pristine silicon is largely inert on its own in the context of gas sensing, unless functionalized with an appropriate gas-sensitive material. We report a chemical-sensitive field-effect transistor (CS-FET) platform based on 3.5-nm-thin silicon channel transistors. Using industry-compatible processing techniques, the conventional electrically active gate stack is replaced by an ultrathin chemical-sensitive layer that is electrically nonconducting and coupled to the 3.5-nm-thin silicon channel. We demonstrate a low-power, sensitive, and selective multiplexed gas sensing technology using this platform by detecting H 2 S, H 2 , and NO 2 at room temperature for environment, health, and safety in the oil and gas industry, offering significant advantages over existing technology. Moreover, the system described here can be readily integrated with mobile electronics for distributed sensor networks in environmental pollution mapping and personal air-quality monitors.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Energy storage: The future enabled by nanomaterials

Lithium-ion batteries, which power portable electronics, electric vehicles, and stationary storage, have been recognized with the 2019 Nobel Prize in chemistry. The development of nanomaterials and their related processing into electrodes and devices can improve the performance and/or development of the existing energy storage systems. We provide a perspective on recent progress in the application of nanomaterials in energy storage devices, such as supercapacitors and batteries. The versatility of nanomaterials can lead to power sources for portable, flexible, foldable, and distributable electronics; electric transportation; and grid-scale storage, as well as integration in living environments and biomedical systems. To overcome limitations of nanomaterials related to high reactivity and chemical instability caused by their high surface area, nanoparticles with different functionalities should be combined in smart architectures on nano- and microscales. The integration of nanomaterials into functional architectures and devices requires the development of advanced manufacturing approaches. We discuss successful strategies and outline a roadmap for the exploitation of nanomaterials for enabling future energy storage applications, such as powering distributed sensor networks and flexible and wearable electronics.

catalysis (heterogeneous)↗
DOE OSTI2019

Urban Deployment Model (UDM) v1.0

The software, called the Urban Deployment Model (UDM), is an integrated set of tools for the simulation and analysis of static and mobile radiation detection systems in complex urban environments. The UDM includes a graphical user interface through which the workflow associated with setting up and executing a simulation may be established. The modular toolsets combine aspects of radiation transport, navigation, graph theory, optimization, and visualization to allow the complete end-to-end simulation of large scale, highly-distributed sensor networks.

Abgrall, Nicolas↗
DOE OSTI2016

General Line Ampacity State Solver

INL’s General Line Ampacity State Solver (GLASS) is a high performance software platform that enables advanced grid system operations and planning efforts to be computed in real time. It enables the combination of advanced sensors and sensor networks, communication and data transfer channels, secure and reliable data management, and real-time processing through a flexible system architecture, with the ability to support and integrate with any utility enterprise system. GLASS is designed to help resolve the problems associated with thermally limited transmission and distribution networks, namely bare overhead power transmission lines. GLASS enables the methodology of Concurrent Cooling (Dynamic Line Rating) by reducing the need of using a cost-prohibited number of weather stations (reduce the number of weather stations per mile of overhead power line) to achieve the resolution necessary for individual electric transmission line span capacity calculations. GLASS achieves this by coupling real-time grid operations data and infrastructure architecture information with real-time field deployed weather station measurements and pre-computed Computational Fluid Dynamics (CFD)-based wind modeling interpolation parameters (look-up tables). GLASS uses mathematical models based on the IEEE 738 standard and builds off of the provided iterative solution using modern software paradigms and programming styles to provide a more robust and modular software system. GLASS also interfaces in real-time with utility companies using known transmission line spans and structures. GLASS provides real-time ampacity calculations based on recent weather station data as well as transmission line specifications. GLASS also allows the user to interact graphically with internal databases, which include information such as transmission line conductor types and thermal rating limits, weather station names and locations, specific transmission line span and structure locations, as well as recent ampacity calculations.

Gentle, Jake↗
DOE OSTI2024

An Accurate and Automated Convective Vortex Detection Method for Long-Duration Infrasound Microbarometer Data

Heating of the surficial layer of the atmosphere often generates convective vortices, known as “dust devils” when they entrain visible debris. Convective vortices are common on both Earth and Mars, where they affect the climate via dust loading, contribute to wind erosion, impact the efficiency of photovoltaic systems, and potentially result in injury and property damage. However, long-duration terrestrial convective vortex activity records are rare. We have developed a high-precision and high-recall method to extract convective vortex signatures from infrasound microbarometer data streams. The techniques utilizes a wavelet-based detector to capture potential events and then a template matching system to extract the duration of the vortex. Since permanent and temporary infrasound sensors networks are present throughout the globe (many with open data), our method unlocks a vast new convective vortex dataset without requiring the deployment of specialized instrumentation.

54 ENVIRONMENTAL SCIENCES↗