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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Stability evaluation and mitigation strategies in advanced tokamaks using 3D MHD spectroscopy

Multi-modal, active 3D MHD spectroscopy is applied in high-performance advanced tokamak scenarios to study their stability time evolution, revealing an intriguing dependence on both and . A tailored applied 3D field provides a 3D plasma response to extract the growth rate of the least stable mode. The estimated growth rate finds a decrease in stability when the minimum in the safety factor (q) passes through 2.0 and reveals inherent risks of crossing an additional rational surface at integer q min , even above the usual q = 1 sawtooth condition. Based on this result, the potential scenario in which q min ~ 2 can be safely crossed during a more stable lower β N phase was investigated, and the improved stability of this scenario is confirmed by the estimated growth rate. This shows that 3D MHD spectroscopy can offer insights into strategies for improving stability by identifying the vulnerable aspects of such scenarios. In addition, the method highlights its potential for instability avoidance by enabling early detection of multiple modes, even before magnetic coils can measure them. The measured growth rate by the 3D MHD spectroscopy shows its reliability by exhibiting a correlation with the programmed rises in plasma beta across various high β N and high q min discharges. In addition, this method is successfully applied during rapidly evolving I p ramp-up phases, a key part of the scenario development. By achieving reasonable growth rate measurements at high-performance scenario developments, this technique contributes to the development of advanced diagnostic tools for tokamak scenario stability, which will help identify an effective pathway to stable, high-performance scenarios.

Yang, S. M. [Princeton Plasma Physics Laboratory (↗
DOE OSTI2023

Coupled Long-Term Experiment and Model Investigation of the Differential Response of Plants and Soil Microbes in a Changing Permafrost Tundra Ecosystem

The major research goal of this project was to understand and quantify the fate of carbon stored in permafrost ecosystems using a combination of field and laboratory experiments to measure and model isotope ratios and carbon fluxes in a tundra ecosystem exposed to experimental warming. Field measurements centered on a two-factor experimental warming to increase air and soil temperatures alone, and in combination, at a tundra field site in Alaska. A second manipulation of water table was embedded within the warming treatment such that both major environmental factors (temperature, moisture) controlling ecosystem carbon dynamics were experimentally altered. The experiment was interfaced with modeling activities using both data assimilation and forward modeling approaches. Models were used to make forecasts of ecosystem carbon dynamics beyond the time frame and environmental space of the experiment itself. This project was a follow-on to previous work that made use of the same field manipulation; here we continued the experimental manipulation in order to test new hypotheses regarding long-term effects of warming and permafrost thaw and subsequent changes in moisture availability on ecosystem carbon dynamics. These results were linked with ongoing synthesis and model intercomparison activities through the Permafrost Carbon Network, which led to additional synthesis publications as a result of collaboration and data sharing from this project. As key outcomes, this project has produced new papers published in the peer-reviewed literature, archived datasets used for model-data intercomparisons, trained graduate students and postdoctoral researchers, and has raised awareness about the vulnerability of permafrost carbon to a wider audience.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Precursor Analysis Report: SQL Slammer Worm Infection of Davis-Besse Nuclear Power Plant 2003

The SQL Slammer Worm Infection of Davis-Besse Nuclear Power Plant 2003 Precursor Analysis Report leverages publicly available information about Davis-Besse’s 2003 cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. On 25 January 2003, the SQL Slammer worm infected more than 90% of vulnerable hosts and crashed the internet in 10 to 15 minutes, making it one of the fastest spreading worms in history. SQL Slammer is a fileless, memory-resident worm that remotely exploits a stack-based buffer overflow vulnerability on local hosts to intensively scan and rapidly self-propagate across the internet. The worm infected approximately 300,000 unpatched hosts running Microsoft Structured Query Language (SQL) Server 2000 or Microsoft Desktop Engine (MSDE) 2000 with SQL Server Resolution Service. The SQL Slammer worm indirectly infected FirstEnergy’s Davis-Besse nuclear power plant by first infecting a consultant’s company network server and then propagating through an external misconfigured connection into Davis-Besse’s site network. The infection caused major network congestion, slow performance, data overloads, and the inability of local hosts to communicate with each other, which eventually caused a loss of availability and a loss of view when the Safety Parameter Display System (SPDS) and Plant Process Computer (PPC) crashed. At the time of the infection, the plant was already offline, the digital monitoring systems had redundant analog backups, and the plant control and safety functions were not affected, so there were no concerns of a safety breach. However, this incident resulted in many lessons learned and spawned important discussions about cybersecurity’s role in nuclear safety and electric power reliability regulation, policy, and guidance. Researchers and analysts identified 10 unique techniques utilized during the attack with a total of 640 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Eight of the identified techniques used during Davis-Besse cyber attack were precursors to the triggering event. Analysis identified 596 observables associated with these precursor techniques, 428 of which were assessed to have an increased likelihood of being perceived in the 331 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS2003

Presumed PDF Modeling of Early Flame Propagation in Moderate to Intense Turbulence Environments

The present paper describes the results obtained from a one-dimensional time dependent numerical technique that simulates early flame propagation in a moderate to intense turbulent environment. Attention is focused on the development of a spark-ignited, premixed, lean methane/air mixture with the unsteady spherical flame propagating in homogeneous and isotropic turbulence. A Monte-Carlo particle tracking method, based upon the method of fractional steps, is utilized to simulate the phenomena represented by a probability density function (PDF) transport equation. Gaussian distributions of fluctuating velocity and fuel concentration are prescribed. Attention is focused on three primary parameters that influence the initial flame kernel growth: the detailed ignition system characteristics, the mixture composition, and the nature of the flow field. The computational results of moderate and intense isotropic turbulence suggests that flames within the distributed reaction zone are not as vulnerable, as traditionally believed, to the adverse effects of increased turbulence intensity. It is also shown that the magnitude of the flame front thickness significantly impacts the turbulent consumption flame speed. Flame conditions studied have fuel equivalence ratio s in the range phi = 0.6 to 0.9 at standard temperature and pressure.

Carmen, Christina↗
NASA NTRS2012

Security Data Warehouse Application

The Security Data Warehouse (SDW) is used to aggregate and correlate all JSC IT security data. This includes IT asset inventory such as operating systems and patch levels, users, user logins, remote access dial-in and VPN, and vulnerability tracking and reporting. The correlation of this data allows for an integrated understanding of current security issues and systems by providing this data in a format that associates it to an individual host. The cornerstone of the SDW is its unique host-mapping algorithm that has undergone extensive field tests, and provides a high degree of accuracy. The algorithm comprises two parts. The first part employs fuzzy logic to derive a best-guess host assignment using incomplete sensor data. The second part is logic to identify and correct errors in the database, based on subsequent, more complete data. Host records are automatically split or merged, as appropriate. The process had to be refined and thoroughly tested before the SDW deployment was feasible. Complexity was increased by adding the dimension of time. The SDW correlates all data with its relationship to time. This lends support to forensic investigations, audits, and overall situational awareness. Another important feature of the SDW architecture is that all of the underlying complexities of the data model and host-mapping algorithm are encapsulated in an easy-to-use and understandable Perl language Application Programming Interface (API). This allows the SDW to be quickly augmented with additional sensors using minimal coding and testing. It also supports rapid generation of ad hoc reports and integration with other information systems.

Vernon, Lynn R.↗
DOE OSTI2022

Impact of Coastal Marsh Eco‐Geomorphologic Change on Saltwater Intrusion Under Future Sea Level Rise

Abstract Coastal saltwater intrusion (SWI) is one key factor that affects the hydrology, ecology, and biogeochemistry of coastal ecosystems. Future climate change, especially intensified sea level rise (SLR), is expected to trigger SWI to encroach on coastal freshwater aquifers more intensively. Numerous studies have investigated decadal/century scale SWI under SLR by assuming a static coastal landscape topography. However, coastal landscapes are highly dynamic in response to SLR, and the impact of coastal landscape evolution on SWI has received very little attention. Thus, this study used a coastal marsh landscape as an example and investigated how coastal marsh evolution affects future SWI with a physically‐based coastal hydro‐eco‐geomorphologic model, Advanced Terrestrial Simulator. Our numerical experiments showed that it is very likely that the marsh elevation increases with future SLR due to sediment deposition, and a depression zone is formed due to different marsh accretion rates between the ocean boundary and the inland. We found that marsh accretion may significantly reduce the surface saltwater inflow at the ocean boundary, and the evolved topographic depression zone may prolong the residence time of surface ponded saltwater, affecting subsurface salinity distribution differently. We also predicted that marshlands may become more sensitive to upland freshwater supply under future SLR, compared with previous predictions without marsh evolution. This study demonstrates the importance of coastal evolution to coastal freshwater‐saltwater interaction. The eco‐geomorphologic effect may not be ignored when evaluating coastal SWI under SLR at decadal or century scales.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Single event upset vulnerability of selected 4K and 16K CMOS static RAM's

Upset thresholds for bulk CMOS and CMOS/SOS RAMS were deduced after bombardment of the devices with 140 MeV Kr, 160 MeV Ar, and 33 MeV O beams in a cyclotron. The trials were performed to test prototype devices intended for space applications, to relate feature size to the critical upset charge, and to check the validity of computer simulation models. The tests were run on 4 and 1 K memory cells with 6 transistors, in either hardened or unhardened configurations. The upset cross sections were calculated to determine the critical charge for upset from the soft errors observed in the irradiated cells. Computer simulations of the critical charge were found to deviate from the experimentally observed variation of the critical charge as the square of the feature size. Modeled values of series resistors decoupling the inverter pairs of memory cells showed that above some minimum resistance value a small increase in resistance produces a large increase in the critical charge, which the experimental data showed to be of questionable validity unless the value is made dependent on the maximum allowed read-write time.

Kolasinski, W. A.↗
DOE OSTI2021

Origins of Acid-Gas Stability Behavior in Zeolitic Imidazolate Frameworks: The Unique High Stability of ZIF-71

Zeolitic imidazolate frameworks (ZIFs) are promising materials for industrial process separations, but recent literature reports have highlighted their vulnerability to acid gases (e.g., SO 2 , CO 2 , NO 2 , H 2 S), often present in practical applications. While previous work has documented the widely varying stability behavior of many ZIFs under varying (humid and dry) acid gas environments, efforts to explain or correlate these experimental observations via empirical descriptors have not succeeded. A key observation is that ZIF-71 (RHO topology) is an extraordinarily stable ZIF material, retaining both structure and porosity under prolonged humid SO 2 exposure whereas many other well-known ZIFs with different linkers and topologies (such as ZIF-8) were shown to degrade. Through a combination of hybrid quantum mechanics/molecular mechanics (QM/MM) based methods and statistical mechanical models, we successfully explain this important experimental observation via atomistic investigations of the reaction mechanism. Our holistic approach reveals an ~9 times lower average defect formation rate in ZIF-71 RHO compared to ZIF-8 SOD, leading to the conclusion that the observed experimental stability of this material rises from kinetic effects. Moreover, our analysis reveals that differing stability of the two materials is determined by the distributions of acid gas molecules, which is difficult to capture using empirical descriptors. Furthermore, our results suggest wider applicability of the present approach, toward identifying tuned functional groups and topologies that move the acid gas distributions away from more reactive sites and thus allow enhanced kinetic stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach

Context: The world is experiencing frequent extreme weather events like droughts, snowstorms, and shifting of seasons due to climate change. Increased frequency and severity of these extreme weather events threaten food security because agriculture depends on climate conditions. Impacts of climate change on the agricultural system not only occur at the grower’s level, but also cascade to other levels along the supply chain. Objective: In this study, we aim to quantify a wide range of economic impacts of different extreme climate events on different stages of a food supply chain. Methods: We chose the potato supply chain in Idaho as a case study. We developed a multi-echelon supply chain simulation model using an agent-based modeling (ABM) approach with five types of agents—farmers, shippers, processors, retailers, and logistics companies. In addition to the business-as-usual (BAU) scenario, we designed two climate-related disruption events—drought and snowstorm. We quantified the heterogeneous impacts at different stages of the supply chain for both fresh and processed potatoes using key performance indicators (KPIs) including revenues, prices, lead times, traded quantities, and food waste quantity. Results and Conclusion: The impacts of the disruption events are different on different agents in the supply chain for different product categories. The price hike of fresh potatoes is far higher than processed potatoes during disruption events. This price hike makes consumers switch to processed potatoes, which require more fresh potatoes as an input that further reinforces the price hike. However, because processed potatoes have an elastic demand, once their prices go up due to higher input cost, their demand drops. Non-contracted farmers gain additional revenues from the disruption events, whereas contracted farmers incur a loss due to lock-in price and lower than usual harvest. Significance: The methodology developed in this study could be applied to other food and agricultural supply chains for understanding the vulnerabilities at agent levels due to climate change disruption events. Furthermore, the findings would help develop mitigation strategies or policies to improve the well-being of the overall supply chain.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Using ACIS on the Chandra X-ray Observatory as a Particle Radiation Monitor II

The Advanced CCD Imaging Spectrometer is an instrument on the Chandra X-ray Observatory. CCDs are vulnerable to radiation damage, particularly by soft protons in the radiation belts and solar storms. The Chandra team has implemented procedures to protect ACIS during high-radiation events including autonomous protection triggered by an on-board radiation monitor. Elevated temperatures have reduced the effectiveness of the on-board monitor. The ACIS team has developed an algorithm which uses data from the CCDs themselves to detect periods of high radiation and a flight software patch to apply this algorithm is currently active on-board the instrument. In this paper, we explore the ACIS response to particle radiation through comparisons to a number of external measures of the radiation environment. We hope to better understand the efficiency of the algorithm as a function of the flux and spectrum of the particles and the time-profile of the radiation event.

Grant, C. E.↗
NASA NTRS2004

SIAM-SERVIR: An Environmental Monitoring and Decision Support System for Mesoamerica

In 2002/2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR) as part of the Mesoamerican Environmental Information System (SIAM). Mesoamerica, composed of the seven Central American countries and the five southernmost states of Mexico, make up only a small fraction of the world's land surface. However, the region is home to seven to eight percent of the planet's biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Today Mesoamerica's biological and cultural diversity is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, together with the University of Alabama in Huntsville (UAH) and the SIAM-SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. In its first year of development and operation, the SIAM-SERVIR project has already yielded valuable information on Central American fires, weather conditions, and the first ever real-time data on red tides. This paper presents the progress thus far in the development of SIAM-SERVIR and the plans for the future.

Irwin, D. E.↗
NASA NTRS2005

SIAM-SERVIR: An Environmental Monitoring and Decision Support System for Mesoamerica

In 2002/2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR) as part of the Mesoamerican Environmental Information System (SIAM). Mesoamerica - composed of the seven Central American countries and the five southernmost states of Mexico - make up only a small fraction of the world s land surface. However, the region is home to seven to eight percent of the planet s biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Today Mesoamerica s biological and cultural diversity is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, together with the University of Alabama in Huntsville (UAH) and the SIAM-SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. In its first year of development and operation, the SIAM-SERVIR project has already yielded valuable information on Central American fires, weather conditions, and the first ever real-time data on red tides. This paper presents the progress thus far in the development of SIAM-SERVIR and the plans for the future.

Irwin, Daniel E.↗
DOE OSTI2026

Modeling Framework for Data Center

This chapter highlights the critical need for advanced modeling of data centers due to their rapidly increasing energy consumption and impact on grid reliability. Driven by the demand for AI applications, data centers are projected to consume a significant portion of US energy by 2028, putting stress on an already challenged power grid. The chapter emphasizes the importance of "fast" time-scale models to understand the dynamic interactions between data centers and the grid, especially given the rapid power fluctuations of AI workloads. It outlines a modeling framework that includes both offline and real-time EMT domain simulations, detailing the necessary representations for various components like utility interfaces, transformers, IT loads, UPS, cooling loads, Battery Energy Storage Systems (BESS), generators, protection systems, and higher-level control systems. While standard simulation tools like PSCAD offer basic models, custom development is often required to accurately capture the unique and fast-changing behaviors of modern data centers. The chapter also discusses key metrics and test cases for validating these models, focusing on transient load responses, protection relay coordination, and demand flexibility. Finally, it addresses the challenges of modeling large-scale data centers, such as computational complexity and the trade-off between model fidelity and practicality, suggesting hybrid modeling approaches as a solution. The overarching goal is to create a robust framework that helps assess data center impacts on grid stability, identify vulnerabilities, and inform the development of standards for reliable integration of these large loads into the bulk power system.

25 ENERGY STORAGE↗
DOE OSTI2021

Cybersecurity concerns for the energy sector in the maritime domain

The world has seen a number of high-profile maritime disasters in recent months and years, and has felt the impact of them. At the same time, the world has also seen a number of high-profile cyberattacks. It has felt their impact, as well. And, likely no sector has been more affected by the maritime and cyber incidents than the energy sector, as fuel prices often spike or trough, and access to energy resources can become an instant source of concern, tension, or even conflict. As energy sectors—in all their forms—continue to rely on the maritime domain or even increase that reliance, they must be mindful that traditional maritime threats—like piracy, theft, and weather events—are not the only threats they face today. Maritime cybersecurity concerns are among the most potentially disruptive to energy-sector interests and, yet, are among the least understood and least addressed. This paper identifies nine areas in which the energy sector faces harmful cyber vulnerabilities in the maritime domain, to provide enough insight and examples to allow for action to be taken to reduce the risk of harm from these different vulnerabilities. The paper develops the example of offshore wind energy to model how to assess cyber considerations more fully. Ultimately, it concludes with a series of recommendations that offer policymakers, energy-sector actors, and security and law-enforcement professionals steps to minimize the exposure of the maritime energy sector to harmful cyberattacks.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

CCE Phase 1: Consequence Prioritization

Idaho National Laboratory (INL) developed the Consequence-driven Cyber-informed Engineering (CCE) methodology to provide public and private organizations with steps to work collaboratively and establish a working relationship to protect critical infrastructure and other national assets. This process is a considerable undertaking, iterative in nature, and—as time and resources allow—should become a part of a company’s culture. By focusing on the impact of potentially negative Events, CCE provides a better understanding of how and why adversaries can affect critical functions and services using cyber-enabled sabotage. This document describes Phase 1 of the CCE process.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2004

Toward Synthesis, Analysis, and Certification of Security Protocols

Implemented security protocols are basically pieces of software which are used to (a) authenticate the other communication partners, (b) establish a secure communication channel between them (using insecure communication media), and (c) transfer data between the communication partners in such a way that these data only available to the desired receiver, but not to anyone else. Such an implementation usually consists of the following components: the protocol-engine, which controls in which sequence the messages of the protocol are sent over the network, and which controls the assembly/disassembly and processing (e.g., decryption) of the data. the cryptographic routines to actually encrypt or decrypt the data (using given keys), and t,he interface to the operating system and to the application. For a correct working of such a security protocol, all of these components must work flawlessly. Many formal-methods based techniques for the analysis of a security protocols have been developed. They range from using specific logics (e.g.: BAN-logic [4], or higher order logics [12] to model checking [2] approaches. In each approach, the analysis tries to prove that no (or at least not a modeled intruder) can get access to secret data. Otherwise, a scenario illustrating the &tack may be produced. Despite the seeming simplicity of security protocols ("only" a few messages are sent between the protocol partners in order to ensure a secure communication), many flaws have been detected. Unfortunately, even a perfect protocol engine does not guarantee flawless working of a security protocol, as incidents show. Many break-ins and security vulnerabilities are caused by exploiting errors in the implementation of the protocol engine or the underlying operating system. Attacks using buffer-overflows are a very common class of such attacks. Errors in the implementation of exception or error handling can open up additional vulnerabilities. For example, on a website with a log-in screen: multiple tries with invalid passwords caused the expected error message (too many retries). but let the user nevertheless pass. Finally, security can be compromised by silly implementation bugs or design decisions. In a commercial VPN software, all calls to the encryption routines were incidentally replaced by stubs, probably during factory testing. The product worked nicely. and the error (an open VPN) would have gone undetected, if a team member had not inspected the low-level traffic out of curiosity. Also, the use secret proprietary encryption routines can backfire, because such algorithms often exhibit weaknesses which can be exploited easily (see e.g., DVD encoding). Summarizing, there is large number of possibilities to make errors which can compromise the security of a protocol. In today s world with short time-to-market and the use of security protocols in open and hostile networks for safety-critical applications (e.g., power or air-traffic control), such slips could lead to catastrophic situations. Thus, formal methods and automatic reasoning techniques should not be used just for the formal proof of absence of an attack, but they ought to be used to provide an end-to-end tool-supported framework for security software. With such an approach all required artifacts (code, documentation, test cases) , formal analyses, and reliable certification will be generated automatically, given a single, high level specification. By a combination of program synthesis, formal protocol analysis, certification; and proof-carrying code, this goal is within practical reach, since all the important technologies for such an approach actually exist and only need to be assembled in the right way.

Schumann, Johann↗
NASA NTRS2021

The Efficacy of Seasonal Terrestrial Water Storage Forecasts for Predicting Vegetation Activity Over Africa

Terrestrial water storage (TWS) provides important information on terrestrial hydroclimate and may have value for seasonal forecasting because of its strong persistence. We use the NASA Hydrological Forecast and Analysis System (NHyFAS) to investigate TWS forecast skill over Africa and assess its value for predicting vegetation activity from satellite estimates of leaf area index (LAI). Forecast skill is high over East and Southern Africa, extending up to 3–6 months in some cases, with more modest skill over West Africa. Highest skill generally occurs during the dry season or beginning of the wet season when TWS anomalies from the previous wet season are most likely to carry forward in time. In East Africa, this occurs prior to and during the transition into the spring “Long Rains” from January–March, while in Southern Africa this period of highest skill starts at the beginning of the dry season in April and extends through to the start of the wet season in October. TWS is highly and positively correlated with LAI, and a logistic regression model shows high cross-validation skill in predicting above or below normal LAI using TWS. Combining the LAI regression model with the NHyFAS forecasts, 1-month lead LAI predictions have high accuracy over East and Southern Africa, with reduced but significant skill at 3-month leads over smaller sub-regions. This highlights the potential value of TWS as an additional source of information for seasonal forecasts over Africa, with direct applications to some of the most vulnerable agricultural regions on the continent.

Terrestrial water shortage↗
DOE OSTI2025

EUREICA: Efficient UltRa Endpoint IoT-enabled Coordinated Architecture

The electricity grid has evolved from a physical system to a cyber-physical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) that include renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. The purpose of this project was to develop a framework ((Efficient, Ultra-REsilient, IoT-Coordinated Assets, or EUREICA)for achieving grid resilience through suitably coordinated assets including a network of Internet of Things (IoT) devices, and a local electricity market (LEM) to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. Experiments conducted during this project demonstrated that, with this SA, a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. The demonstrations were carried out using a variety of high-fidelity co-simulation platforms, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

14 SOLAR ENERGY↗