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DOE OSTI2022

Anticipating water distribution service outages from increasing temperatures

With projected temperature increases and extreme events due to climate change for many regions of the world, characterizing the impacts of these emerging hazards on water distribution systems is necessary to identify and prioritize adaptation strategies for ensuring reliability. To aid decision-making, new insights are needed into how water distribution system reliability to climate-driven heat will change, and the proactive maintenance strategies available to combat failures. To this end, we present the model Perses, a framework that joins a water distribution network hydraulic solver with reliability models of physical assets or components to estimate temperature increase-driven failures and resulting service outages in the long term. A theoretical case study is developed using Phoenix, Arizona temperature profiles, a city with extreme temperatures and a rapidly expanding infrastructure. By end-of-century under hotter futures there are projected to be 1%–5% more pump failures, 2%–5% more PVC pipe failures, and 3%–7% more iron pipe failures (RCP 4.5–8.5) than a baseline historical temperature profile. Service outages, which constitute inadequate pressure for domestic and commercial use are projected to increase by 16%–26% above the baseline under maximum temperature conditions. The exceedance of baseline failures, when compounded across a large metro region, reveals potential challenges for budgeting, management, and maintenance. An exploration of the mitigation potential of adaptation strategies shows that expedited repair times are capable of offsetting the additional outages from climate change, but will come with a cost.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Bond-rearrangement and ionization mechanisms in the photo-double-ionization of simple hydrocarbons (C 2 H 4 , C 2 H 3 F, and 1,1-C 2 H 2 F 2 ) near and above threshold

We have investigated bond-rearrangement driven by photo-double-ionization (PDI) near and above the double ionization threshold in a sequence of carbon-carbon double bonded hydrocarbon molecules: ethylene, fluoroethylene, and 1,1-difluoroethylene. We employ the kinematically complete cold target recoil ion momentum spectroscopy (COLTRIMS) method to resolve all photo-double-ionization events leading to two-ionic fragments. We observe changes in the branching ratios of different dissociative ionization channels depending on the presence of none, one, or two fluorine atoms. The role of the fluorine atom in the bond-rearrangement channels is intriguing as evident by the re-ordering of the threshold energies of the PDI in the fluorinated molecules. These effects offer a compelling argument that the electronegativity of the fluorine (or the polarity of the molecule) strongly influences the potential energy surfaces of the molcules and drives bond-rearrangement during the dissociation process. The energy sharing and the relative angle between the 3D-momentum vectors of the two electrons provide clear evidence of direct and indirect PDI processes.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2018

Stochastic Generation Capacity Expansion Planning with Approximate Dynamic Programming

Failing to consider the many long-term uncertainties that affect the performance of a power generation portfolio can result in suboptimal generation expansion plans. Further, traditional deterministic approaches can omit flexible plans that are able to adapt to future events. In this paper, we explore the use of approximate dynamic programming (ADP) to create forward-looking generation expansion plans. A case study is included with three sequential decision periods; three generation technologies; and four uncertainties: demand growth, natural gas prices, renewable portfolio standards, and the adoption of customer-driven solar generation. The flexible plans found through ADP show a 3 % reduction in total expected cost when compared to myopic planning heuristics while circumventing the computational burdens that accompany high-dimensional dynamic programs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

How Low Can You Go? Using Synthetic 3D Imagery to Drastically Reduce Real-World Training Data for Object Detection

Deep convolutional neural networks (DCNNs) currently provide state-of-the-art performance on image classification and object detection tasks, and there are many global security mission areas where such models could be extremely useful. Crucially, the success of these models is driven in large part by the widespread availability of high-quality open source data sets such as Image Net, Common Objects in Context (COCO), and KITTI, which contain millions of images with thousands of unique labels. However, global security relevant objects-of-interest can be difficult to obtain: relevant events are low frequency and high consequence; the content of relevant images is sensitive; and adversaries and proliferators seek to obscure their activities. For these cases where exemplar data is hard to come-by, even fine-tuning an existing model with available data can be effectively impossible. Recent work demonstrated that models can be trained using a combination of real-world and synthetic images generated from 3D representations; that such models can exceed the performance of models trained using real-world data alone; and that the generated images need not be perfectly realistic (Tremblay, et al., 2018). However, this approach still required hundreds to thousands of real-world images for training and fine tuning, which for sparse, global security-relevant datasets can be an unrealistic hurdle. In this research, we validate the performance and behavior of DCNN models as we drive the number of real-world images used for training object detection tasks down to a minimal set. We perform multiple experiments to identify the best approach to train DCNNs from an extremely small set of real-world images. In doing so, we: Develop state-of-the-art, parameterized 3D models based on real-world images and sample from their parameters to increase the variance in synthetic image training data; Use machine learning explainability techniques to highlight and correct through targeted training the biases that result from training using completely synthetic images; and Validate our results by comparing the performance of the models trained on synthetic data to one another, and to a control model created by fine-tuning an existing ImageNet-trained model with a limited number (hundreds) of real-world images.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2005

Interannual Variations in Tropical Upper-Tropospheric Humidity: Understanding Tropical Convective and Dynamical Processes

Uncertainty remains as to what extent variability in mid to upper tropospheric moisture, especially over the tropics, behaves as constant relative humidity during interannual climate variations associated with ENSO. Systematic variations in HIRS 6.7 micron and MLS 205 GHz suggest that dry subtropical regions evolving during warm SST events depress relative humidity, but the interpretation of these events is still uncertain. Additional specific concerns have to do with regional signatures of convective processes: How does the origin of dry air in the eastern subtropical N. Pacific differ in ENSO warm versus cold years? The dynamics of Rossby wave forcing by convective heating, subtropical jet stream dynamics, and dynamics driven subsidence all come into play here. How variations in precipitating ice hydrometeors from tropical anvils relate to variations in UTH is also a subject of debate? Do variations in precipitating ice, cloud cover and water vapor behavior show any support for the Iris-hypothesis mechanism? Here we examine historical records of SSM/T-2 data to gain a better physical understanding of the effects of deep convective moisture sources and dynamically-induced vertical circulations on UTH. These high frequency microwave measurements (183.3 GHz) take advantage of far less sensitivity to cloud hydrometeors than the 6.7 micron data to yield a record of upper tropospheric relative humidity. Furthermore, signatures of precipitating ice from these channels facilitate comparisons to TRMM hydrometeors detected by radar. In analyzing these observations, we isolate water vapor and temperature change components that affect brightness temperatures and the inferred relative humidity. Trajectory modeling is also used to understand interannual humidity anomalies in terms of outflow fbm convective regions and history of diabatically-driven sinking which modifies relative humidity.

Robertson, Franklin R.↗

NASA NTRSDate not supplied

How Autonomous Intelligent Systems Can Facilitate Earth-independent Medical Care: Going Beyond Telepresence

During the last decade, teleoperated robotic systems have extended humans’ sensorimotor competence to digitally fly beyond the physical barrier of distance and scale and thus transmit sensorimotor skills of the human through direct communication. Telepresence capabilities have enabled tele-physical remote access at small scales thanks to telerobotic mediums. Although the concept was initially motivated by space applications, such technologies quickly have expanded into the medical domain and resulted in teleoperated medical robots, including telerobotic surgical systems (such as the da Vinci surgical system). Effective telepresence fundamentally depends on an agile, reliable, and secure communication medium that can transmit real-time information between the operator and a remote device. However, direct telepresence may not be achievable for long-duration exploration spaceflight missions. Thus, autonomous systems and local intelligence represent potential solutions to the aforementioned issues. One example solution employs demonstration systems which enable learning from the pre-captured inputs of a skilled human operator. These will be computationally modeled and later probabilistically replicated toward the completion of remote physical tasks when direct telepresence is not viable - such as under communication blackout conditions. In other words, trained autonomous systems (e.g., robots) can perform remote operations that mimic the physical performance of experts during remote operations/training. Beyond learning the physics of the task, autonomous agents can also be used to conduct algorithmic decision-making that mimics the higher-level cognition of the expert. Thus, using an autonomous system, pre-trained cognitive and manipulation-based skills can be leveraged (acquired during pre-mission events) to produce digital twins of an intelligent operator. Such systems can be used for the real-time conduction of intricate tasks in complex and unstructured environments. Such systems will operationalize “cognitive digital twins” and can expand the reach of human cognition and manipulation through the power of data-driven learning from demonstration algorithms. This system category will be discussed as a fully autonomous operation in this talk. In addition to the above, we will also propose and discuss the possibility of partial-automation using remote intelligence and remote sensing. In contrast to full automation, partial automation can close the loop through a local operator equipped with augmented sensory awareness through wearable systems. Such technologies will allow the local operator to conduct delicate tasks while being guided using sensory augmentation and being monitored to gauge her/his level of cognitive focus and performance. The difference with the previous category is that a remote human will conduct the task. Further, rather than making a digital twin of human cognition, we will augment the control inputs of the local human to match those of the skilled expert operator who is not accessible in real-time. Going beyond classic telepresence and thus approaching intelligent telepresence, our vision is that autonomous agents will eventually enable the safe, consistent and efficient delivery of complex, remote and smart medical care during space exploration across operators in an Earth-independent fashion. We will discuss our collective vision from NASA and MERIIT@NYU lab in this talk.

Telepresence↗

NASA NTRS2022

Strong Reconnection Electric Fields in Shock-Driven Turbulence

Turbulent magnetic reconnection in a quasi-parallel shock under parameters relevant to the Earth's bow shock is investigated by means of a two-dimensional particle-in-cell simulation. The addressed aspects include the reconnection electric field, the reconnection rate, and the electron and the ion outflow speeds. In the shock transition region, many current sheets are generated in shock-driven turbulence, and electron-only reconnection and reconnection where both ions and electrons are involved can occur in those current sheets. The electron outflow speed in electron-only reconnection shows a positive correlation with the theoretical speed, which is close to the local electron Alfvén speed, and a strong convection electric field is generated by the large electron outflow. As a result, the reconnection electric field becomes much larger than those in the standard magnetopause or magnetotail reconnection. In shock-driven reconnection that involves ion dynamics, both electron outflows and ion outflows can reach of the order of 10 times the Alfvén speed in the X-line rest frame, leading to a reconnection electric field the same order as that in electron-only reconnection. An electron-only reconnection event observed by the magnetospheric multiscale mission downstream of a quasi-parallel shock is qualitatively similar to those in the simulation and shows that the outflow speed reaches approximately half the local electron Alfvén speed, supporting the simulation prediction.

magnetic reconnection↗

NASA NTRSDate not supplied

Enabling API Access to the Space Weather Services at the Community Coordinated Modeling Center

Over the span of 20 years, the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) has been leading a number of community-driven services and applications that provide a free and open access to the cutting-edge space weather and Heliophysics models through a simple web-based interface. CCMC also oversees an open archive of user model simulations and related metadata, maintains space weather-related data streams, curates validation and event datasets, and more. To maximize utility of its complementary services and data holdings, CCMC has been gradually building up an ad-hoc set of interfaces and specifications that facilitate coupling and interconnection within the organization, while also simplifying management and monitoring of the data. As the models continue to grow in maturity and complexity, CCMC is looking to reduce the complexity for its end users by making public some of the internal APIs as well as implementing dedicated interfaces as required by the community. In this presentation, we will overview the current run services at CCMC and will describe our current and near-future efforts in providing interfaces to these services.

space weather↗

DOE OSTI2018

Assessing 21st century contaminants of concern using integrative passive sampling devices to obtain more meaningful and cost-effective data on impacts from stormwater runoff

In many cases stormwater compliance monitoring is labor intensive, expensive, and largely unsuccessful in providing the data needed to support stormwater management goals. In addition, data from manual grab sampling and automated composite sampling are rarely collected in a manner that provides the information required to identify sources of contamination, evaluate the effectiveness of Best Management Practices, or inform effective decision making. Furthermore, monitoring is often driven by the need to meet low concentration benchmarks for metals and other constituents that do not take into account loading into the receiving waters, resulting in arbitrary monitoring requirements (monthly or seasonally) that are not tied to the driving forces within the watershed such as hydrology (flow regime), weather (storm events and antecedent dry periods), and upland land use and cover (Rosen and Johnston 2015, US Navy 2016).

stormwater, passive samplers, trace metals↗

DOE OSTI2024

Data-driven and model-agnostic approach to solving combinatorial assignment problems in searches for new physics

We present a novel approach to solving combinatorial assignment problems in particle physics. The correct assignment of decay products to parent particles is achieved in a model-agnostic fashion by introducing a neural network architecture, asswd-, which combines a custom layer based on attention mechanisms and dual autoencoders. We demonstrate how the network, trained purely on background events in an unsupervised setting, is capable of reconstructing correctly hypothetical new particles regardless of their mass, decay multiplicity, and substructure, and produces simultaneously an anomaly score that can be used to efficiently suppress the background. This model allows the extension of the suite of searches for localized excesses to include nonresonant particle pair production where the reconstruction of the two resonant masses is thwarted by combinatorics. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

NASA NTRS2022

Data-driven Expectations for Electromagnetic Counterpart Searches Based on LIGO/Virgo Public Alerts

Searches for electromagnetic counterparts of gravitational-wave signals have redoubled since the first detection in2017 of a binary neutron star merger with a gamma-ray burst, optical/infrared kilonova, and panchromatic after glow. Yet, one LIGO/Virgo observing run later, there has not yet been a second, secure identification of an electromagnetic counterpart. This is not surprising given that the localization uncertainties of events in LIGO and Virgo’s third observing run, O3, were much larger than predicted. We explain this by showing that improvements in data analysis that now allow LIGO/Virgo to detect weaker and hence more poorly localized events have increased the overall number of detections, of which well-localized, gold-plated events make up a smaller proportion overall. We present simulations of the next two LIGO/Virgo/KAGRA observing runs, O4 and O5, that are grounded in the statistics ofO3 public alerts. To illustrate the significant impact that the updated predictions can have, we study the follow-up strategy for the Zwicky Transient Facility. Realistic and timely forecasting of gravitational-wave localization accuracy is paramount given the large commitments of telescope time and the need to prioritize which events are followed up. We include a data release of our simulated localizations as a public proposal planning resource for astronomers

Polina Petrov↗

DOE OSTI2018

The Alfvénic nature of energy transfer mediation in localized, strongly nonlinear Alfvén wavepacket collisions

In space and astrophysical plasmas, violent events or instabilities inject energy into turbulent motions at large scales. Nonlinear interactions among the turbulent fluctuations drive a cascade of energy to small perpendicular scales at which the energy is ultimately converted into plasma heat. Previous work with the incompressible magnetohydrodynamic (MHD) equations has shown that this turbulent energy cascade is driven by the nonlinear interaction between counterpropagating Alfvén waves – also known as Alfvén wave collisions. Direct numerical simulations of weakly collisional plasma turbulence enables deeper insight into the nature of the nonlinear interactions underlying the turbulent cascade of energy. In this paper, we directly compare four cases: both periodic and localized Alfvén wave collisions in the weakly and strongly nonlinear limits. Our results reveal that in the more realistic case of localized Alfvén wave collisions (rather than the periodic case), all nonlinearly generated fluctuations are Alfvén waves, which mediates nonlinear energy transfer to smaller perpendicular scales.

Physics↗

DOE OSTI2018

Non-Routine Event Detection and Adjustment (NRE) v1

The non-routine event (NRE) detection and adjustment module provides algorithms to detect and to adjust changes in energy use that are not attributable to installed efficiency measures, and not accounted for in the baseline model's independent variables. The detection algorithm is based on statistical change point algorithm and the adjustment uses a data driven approach to quantify the changes in the energy use that are induced by the NRE.

Granderson, Jessica↗

DOE OSTI2026

Strategic Energy Plan: Playa de Ponce, Ponce, Puerto Rico

Un Nuevo Amanecer Inc. (UNA), a community-based NGO (501C(3)), sought technical assistance through the U.S. Department of Energy's (DOE's) Energy Technology Innovation Partnership Project (ETIPP) to develop a strategic energy plan (SEP) for the community of Playa de Ponce on the south coast of Puerto Rico. A SEP helps communities identify energy goals and priority projects, and outline strategies and actions to build a shared path toward their energy vision. The primary goal of this SEP is to collaboratively explore pathways for the community's energy future. Researchers from the National Laboratory of the Rockies (NLR) engaged with the community for a period of seven months and facilitated a series of in-person community engagement workshops along with ETIPP regional partner Puerto Rico Hispanic Federation, UNA, and community leaders. The SEP workshops were held twice, March 18-20 and June 24-26, 2025. Through facilitated discussions, the community worked together to define and articulate a clear vision for its short-, medium-, and long-term energy goals. The workshops played a key role in identifying the specific strategies and priority projects that would best suit the needs of the community. The discussions outlined the community's energy aspirations, establishing a shared vision, setting goals, and outlining the priority actions needed to bring them to fruition. During the workshops, the community shared some of the most pressing energy challenges that they face on a regular basis, such as high energy costs that disproportionately impact an aging population and unreliable electricity during extreme weather events that result in frequent power outages. These issues have also exacerbated risks to public health and safety of the community. In response, UNA requested technical assistance through ETIPP to inform the development of a SEP tailored to Playa de Ponce to support its energy vision. This document explores four community-driven energy strategies aligned with that vision. Figure 1 shows the strategies outlined in this plan, which are categorized into three focus areas as identified by the community: energy reliability; safety and security; and stakeholder participation, education, and capacity building. This document serves as a shared roadmap for developing and implementing energy solutions that meet the needs of Playa de Ponce. It is intended to serve as a public resource for the community, UNA, and local authorities - providing tools, information and a shared foundation to inform future implementation efforts. This plan is intended to complement ongoing planning frameworks at the municipal, regional, and island-wide levels. As a living document, this SEP can evolve alongside Playa de Ponce's changing energy goals, while offering a framework to help them realize their energy vision.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Analysis of Organophosphorus-Based Nerve Agent Degradation Products by Gas Chromatography-Mass Spectrometry (GC-MS): Current Derivatization Reactions in the Analytical Chemist’s Toolbox

The field of gas chromatography-mass spectrometry (GC-MS) in the analysis of chemical warfare agents (CWAs), specifically those involving the organophosphorus-based nerve agents (OPNAs), is a continually evolving and dynamic area of research. The ever-present interest in this field within analytical chemistry is driven by the constant threat posed by these lethal CWAs, highlighted by their use during the Tokyo subway attack in 1995, their deliberate use on civilians in Syria in 2013, and their use in the poisoning of Sergei and Yulia Skripal in Great Britain in 2018 and Alexei Navalny in 2020. These events coupled with their potential for mass destruction only serve to stress the importance of developing methods for their rapid and unambiguous detection. Although the direct detection of OPNAs is possible by GC-MS, in most instances, the analytical chemist must rely on the detection of the products arising from their degradation. To this end, derivatization reactions mainly in the form of silylations and alkylations employing a vast array of reagents have played a pivotal role in the efficient detection of these products that can be used retrospectively to identify the original OPNA.

sarin↗

DOE OSTI2017

Revealing Physical Activity of GRB Central Engine with Macronova/Kilonova Data

The modeling of Li-Paczyński macronova/kilonova signals gives a reasonable estimate on the neutron-rich material ejected during the neutron star mergers. Usually the accretion disk is more massive than the macronova ejecta, with which the efficiencies of converting the disk mass into prompt emission of three merger-driven GRBs can hence be directly constrained. Supposing the macronovae/kilonovae associated with GRB 050709, GRB 060614, and GRB 130603B arose from radioactive decay of the r -process material, the upper limit on energy conversion efficiencies are found to be as low as ∼10{sup −6}–10{sup −4}. Moreover, for all three events, neutrino annihilation is likely powerful enough to account for the brief gamma-ray flashes. Neutrino annihilation can also explain the “extended” emission lasting ∼100 s in GRB 050709, but does not work for the one in GRB 060614. These progresses demonstrate that the macronova can serve as a novel probe of the central engine activity.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1992

Building vibrations induced by noise from rotorcraft and propeller aircraft flyovers

Noise and building vibrations were measured for a series of helicopter and propeller-driven aircraft flyovers at WFF during May 1978. The building response data are compared with similar data acquired earlier at sites near Dulles and Kennedy Airports for operation of commercial jet transports, including the Concorde supersonic transport. Results show that noise-induced vibration levels in windows and walls are directly proportional to sound pressure level and that for a given noise level, the acceleration levels induced by a helicopter or a propeller-driven aircraft flyover cannot be distinguished from the acceleration levels induced by a commercial jet transport flyover. Noise-induced building acceleration levels were found to be lower than those levels which might be expected to cause structural damage and were also lower than some acceleration levels induced by such common domestic events as closing windows and doors.

Shepherd, Kevin P.↗

NASA NTRS1997

Interannual Variability in Soil Trace Gas (CO2, N2O, NO) Fluxes and Analysis of Controllers

Interannual variability in flux rates of biogenic trace gases must be quantified in order to understand the differences between short-term trends and actual long-term change in biosphere-atmosphere interactions. We simulated interannual patterns (1983-1988) of global trace gas fluxes from soils using the NASA Ames model version of CASA (Carnegie-Ames-Stanford Approach) in a transient simulation mode. This ecosystem model has been recalibrated for simulations driven by satellite vegetation index data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) over the mid-1980s. The predicted interannual pattern of soil heterotropic CO2 emissions indicates that relatively large increases in global carbon flux from soils occurred about three years following the strong El Nino Southern Oscillation (ENSO) event of 1983. Results for the years 1986 and 1987 showed an annual increment of +1 Pg (1015 g) C-CO2 emitted from soils, which tended to dampen the estimated global increase in net ecosystem production with about a two year lag period relative to plant carbon fixation. Zonal discrimination of model results implies that 80-90 percent of the yearly positive increments in soil CO2 emission during 1986-87 were attributable to soil organic matter decomposition in the low-latitudes (between 30 N and 30 S). Soils of the northern middle-latitude zone (between 30 N and 60 N) accounted for the residual of these annual increments. Total annual emissions of nitrogen trace gases (N2O and NO) from soils were estimated to vary from 2-4 percent over the time period modeled, a level of variability which is consistent with predicted interannual fluctuations in global soil CO2 fluxes. Interannual variability of precipitation in tropical and subtropical zones (30 N to 20 S appeared to drive the dynamic inverse relationship between higher annual emissions of NO versus emissions of N2O. Global mean emission rates from natural (heterotrophic) soil sources over the period modeled (1983-1988) were estimated at 57.1 Pg C-CO2yr-1, 9.8Tg (1012 g) N-NO yr-1, and 9.7 Tg N-N2O yr-1. Chemical fertilizer contributions to global soil N gas fluxes were estimated at between 1.3 to 7.3 Tg N-NO yr-1, and 1.2 to 4.0 Tg N-N2O yr-1.

Potter, C.↗