Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Human System”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Biophotonic rogue waves in red blood cell suspensions

Rogue waves are ubiquitous in nature, appearing in a variety of physical systems ranging from acoustics, microwave cavities, optical fibers, and resonators to plasmas, superfluids, and Bose–Einstein condensates. Unlike nonlinear solitary waves, rogue waves are extreme events that can occur even without nonlinearity by, for example, spontaneous synchronization of waves with different spatial frequencies in a linear system. Here, we report the observation of rogue-wave-like events in human red blood cell (RBC) suspensions under weak light illumination, characterized by an abnormal L-shaped probability distribution. Such biophotonic extreme events arise mostly due to the constructive interference of Mie-scattered waves from the suspended RBCs, whose biconcave shape and mutable orientation give rise to a time-dependent random phase modulation to an incident laser beam. We numerically simulate the beam propagation through the colloidal suspensions with added disorder in both spatial and temporal domains to mimic random scattering due to Brownian motion. In addition, at high power levels, nonlinear beam self-focusing is also observed, leading to a dual-exponential probability distribution associated with the formation of multiple soliton-like spots. Such rogue wave events should also exist in environments with cells of other species such as swimming bacteria, and understanding of their underlying physics may lead to unexpected biophotonic applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Artificial Intelligence Application to D and D - 20492

As aging facilities across the DOE complex await decommissioning, there is an ongoing need to understand any changes in the structural conditions. Many of these facilities were built over 50 years ago and, in some cases, these facilities have gone beyond the expected operational lifetime. Many facilities have been placed in a state of 'cold and dark,' sitting unused and awaiting decommissioning. Especially challenging are the aging facilities that provide unique operational/production capabilities to support critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may become compromised as time passes. It is critical that adequate inspections be performed on a continual basis and that the data collected undergoes sufficient analysis to support timely identification of any new or worsening structural issues as well as prompt needed maintenance and repairs to maintain the facilities in a safe condition. In recent days, Artificial Intelligence (AI) [1] and its application to various domains are growing at fast speed. FIU is performing research in this area and exploring the associated technologies to solve nuclear decommissioning problems. Artificial intelligence refers to the capability of a program to autonomously act, react and adapt to the working environment. AI enables the machine to behave like humans and perform the cognitive functions such as 'learning' and 'problem solving'. AI systems gradually moving from traditional approaches (algorithms and expert systems) towards more efficient and advanced technologies (machine learning [1] and deep learning [2] [3]). AI is the study of algorithms and statistical models that is being used by computers to perform specific tasks without using explicit instructions. FIU is working to develop a pilot-scale infrastructure to implement structural health monitoring using AI technologies with focus on machine learning, deep learning. This research is focused on Computer Vision/Image Classification area of AI applications. This can also be expanded to other areas of AI related to Object Recognition and Character Recognition in images. In addition to utilizing existing data sets, FIU will collect and investigate image and video data using FIU test-bed mockups to monitor structural health of the facility. Resulting data will be processed and analyzed using machine learning/deep learning technologies. The proposed pilot system is intended to serve as a starting point to engage the DOE field sites on related data sets and their decision making needs. It is anticipated that proposed machine learning/deep learning technologies can be effectively employed using anomaly detection to solve EM challenges in surveillance and maintenance of the D and D facilities. FIU will work with research stakeholders to identify applications at various sites and other DOE facilities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Towards Agentic AI on Particle Accelerators

As particle accelerators grow in complexity, traditional control methods face increasing challenges in achieving optimal performance. This paper envisions a paradigm shift: a decentralized multi-agent framework for accelerator control, powered by Large Language Models (LLMs) and distributed among autonomous agents. We present a proposition of a self-improving decentralized system where intelligent agents handle high-level tasks and communication and each agent is specialized control individual accelerator components. This approach raises some questions: What are the future applications of AI in particle accelerators? How can we implement an autonomous complex system such as a particle accelerator where agents gradually improve through experience and human feedback? What are the implications of integrating a human-in-the-loop component for labeling operational data and providing expert guidance? We show two examples, where we demonstrate viability of such architecture.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Modbus RTU for Embedded Cyber Secure Inverter Controller

The Modbus communication protocol is a widely adopted communication standard in industrial control systems. This communication protocol is known for being reliable and straightforward to implement while being versatile in terms of its operating parameters while supporting multiple formats over various hardware infrastructures and architectures. Many intelligent devices such as Programmable Logic Controllers (PLCs), Human-Machine Interfaces (HMIs), Internet-of-Things (IoT), and various Operational Technologies (OT) utilize Modbus for their communication systems. These types of systems must communicate with each other through a standardized and central communication process. To support the integration of these modular systems, a Field-Programmable Gate Array (FPGA) can act as an embedded central routing fabric for this communication to take place. Embedded systems are versatile enough to interface with various devices and systems to accomplish various goals. Additionally, embedded systems require relatively small physical designs to minimize the required resources to facilitate the intended application by providing low-level system access. This minimization of system resources goes hand in hand with reducing the financial cost of a proposed solution or system. As remotely collaborating researchers often use FPGAs to prototype designs that are required to have a method for data transmission among systems, it is imperative to provide a baseline standard for communications among devices and systems. A typical method of implementing the Modbus RTU communication protocol in an embedded environment is using integrated logic architectures within the FPGA called “Intellectual Property (IP) cores.” IP cores can be designed using integrated logic or circuit designs to function as an embedded processor. These IP cores can then perform the required computational actions to support the Modbus RTU communication protocol by utilizing high-level programming languages such as the C programming language. The hardware description language of Very High-Speed Integrated Circuit Hardware Description Language (VHDL) allows for the control of real hardware at the logic gate and signal level. These logic gates and signals can be designed and controlled to perform desired actions based on the system design. Programming an FPGA using VHDL allows an individual to access the lowest abstraction level of the system during FPGA development. This level of abstraction is referred to as the register-transfer level (RTL), which gives access to manipulating values and variables at the register level. This register-level manipulation provides precision over creating the logical circuit within the FPGA, thus minimizing the required code to perform desired operations. The Modbus RTU communication protocol can be implemented within an FPGA using VHDL programming to establish a standardized and embedded serial communication pathway. This implementation provides a standardized communication protocol to streamline research efforts among researchers, thus increasing the efficiency of research efforts. Additionally, this Modbus RTU implementation requires fewer resources when compared to typical communication protocol implementations that utilize an IP core, reducing the hardware requirement for effective research efforts.

communication↗
DOE OSTI2021

Using Qualified On-Site Nuclear Power Plant Simulators in Human Factors Validations of Control Room Upgrades

Existing commercial nuclear power plants (NPPs) are valuable assets in the infrastructure portfolio of the United States (U.S.) because they safely and reliably generate about 1/5th of all the electricity used. The instrumentation and control (I&C) systems in commercial NPPs are the ‘eyes and ears' of the operator, allowing operators to maintain situation awareness, thereby allowing the plant to operate safely and efficiently for all phases of operation. Because the I&C systems in NPPs are still mostly based on analog technologies, which are reliable but not especially cost-effective, upgrading the existing I&C in com-mercial NPPs to new digital I&C is very important. Furthermore, simulators and simulation are critical human factors engineering tools for this I&C modernization work. NPP control room simulators are essential test beds to simulate normal, abnormal, and emergency operations that allow human factors researchers to safely and realistically evaluate early design phase prototypes of the upgraded digital I&C, and validate final as-built digital I&C systems that have been modernized deployed in NPPs. This paper describes research performed using qualified on-site NPP simulators to perform human factors validations of digital I&C control room upgrades.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Design Philosophy for Accelerator Control Rooms

This report describes the foundational human factors principles needed to design user interfaces for accelerator control rooms. These principles are presented as recommendations for accelerator control system interface design and are illustrated with examples drawn from accelerator operations at Fermi National Accelerator Laboratory (Fermilab). These high-level principles are intended to serve as design objectives that apply generally across all control system interfaces developed for the accelerator complex. This design philosophy document is a high-level roadmap to approach the general interface design for the accelerator complex. This philosophy applies state-of-the-art human factors principles and evidence-based design standards to an accelerator environment, which will transform the next era of accelerator interfaces as outlined by the Accelerator Controls Operations Research Network (ACORN) Project. Further work will include mapping the general design principles included in this report to more specific guidance in the form of a user interface style guide.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Early Holocene cold snaps and their expression in the moraine record of the eastern European Alps

Glaciers preserve climate variations in their geological and geomorphological records, which makes them prime candidates for climate reconstructions. Investigating the glacier–climate system over the past millennia is particularly relevant first because the amplitude and frequency of natural climate variability during the Holocene provides the climatic context against which modern, human-induced climate change must be assessed. Second, the transition from the last glacial to the current interglacial promises important insights into the climate system during warming, which is of particular interest with respect to ongoing climate change. Evidence of stable ice margin positions that record cooling during the past 12 kyr are preserved in two glaciated valleys of the Silvretta Massif in the eastern European Alps, the Jamtal (JAM) and the Laraintal (LAR). We mapped and dated moraines in these catchments including historical ridges using beryllium-10 surface exposure dating (10Be SED) techniques and correlate resulting moraine formation intervals with climate proxy records to evaluate the spatial and temporal scale of these cold phases. The new geochronologies indicate the formation of moraines during the early Holocene (EH), ca. 11.0 ± 0.7 ka (n = 19). Boulder ages along historical moraines (n = 6) suggest at least two glacier advances during the Little Ice Age (LIA; ca. 1250–1850 CE) around 1300 CE and in the second half of the 18th century. An earlier advance to the same position may have occurred around 500 CE. The Jamtal and Laraintal moraine chronologies provide evidence that millennial-scale EH warming was superimposed by centennial-scale cooling. The timing of EH moraine formation coincides with brief temperature drops identified in local and regional paleoproxy records, most prominently with the Preboreal Oscillation (PBO) and is consistent with moraine deposition in other catchments in the European Alps and in the Arctic region. This consistency points to cooling beyond the local scale and therefore a regional or even hemispheric climate driver. Freshwater input sourced from the Laurentide Ice Sheet (LIS), which changed circulation patterns in the North Atlantic, is a plausible explanation for EH cooling and moraine formation in the Nordic region and in Europe.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Overcoming persistent challenges in putting environmental flow policy into practice: a systematic review and bibliometric analysis

The implementation of environmental flows (e-flows) aims to reduce the negative impacts of hydrological alteration on freshwater ecosystems. Despite the growing attention to the importance of e-flows since the 1970s, actual implementation has lagged. Therefore, we explore the limitations in e-flows implementation, their systemic reasons, and solutions. We conducted a systematic review and a bibliometric analysis to identify peer-reviewed articles published on the topic of e-flows implementation research in the last two decades, resulting in 68 research and review papers. Co-occurrence of terms, and geographic and temporal trends were analyzed to identify the gaps in environmental water management and propose recommendations to address limitations on e-flows implementation. We identify the underlying causes and potential solutions to such challenges in environmental water management. The limitations to e-flow implementation identified were categorized into 21 classes. The most recognized limitation was the competing priorities of human uses of water (n = 29). Many secondary limitations, generally co-occurring in co-causation, were identified as limiting factors, especially for implementing more nuanced and sophisticated e-flows. The lack of adequate hydrological data (n = 24) and ecological data (n = 28) were among the most mentioned, and ultimately lead to difficulties in starting or continuing monitoring/adaptive management (n = 28) efforts. The lack of resource/capacity (n = 21), experimentation (n = 19), regulatory enforcement (n = 17), and differing authorities involved (n = 18) were also recurrent problems, driven by the deficiencies in the relative importance given to e-flows when facing other human priorities. In order to provide a clearer path for successful e-flow implementation, system mapping can be used as a starting point and general-purpose resource for understanding the sociohydrological problems, interactions, and inherited complexity of river systems. Secondly, we recommend a system analysis approach to address competing demands, especially with the use of coupled water-energy modeling tools to support decision-making when hydropower generation is involved. Such approaches can better assess the complex interactions among the hydrologic, ecological, socioeconomic, and engineering dimensions of water resource systems and their effective management. Lastly, given the complexities in environmental water allocation, implementation requires both scientific rigor and proven utility. Consequently, and where possible, we recommend a move from simplistic flow allocations to a more holistic approach informed by hydroecological principles. To ease conflicts between competing water demands, water managers can realize more 'pop per drop' by supporting key components of a flow regime that include functional attributes and processes that enhance biogeochemical cycling, structural habitat formation, and ecosystem maintenance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Reducing nighttime light exposure in the urban environment to benefit human health and society

Nocturnal light pollution can have profound effects on humans and other organisms. Recent research indicates that nighttime outdoor lighting is increasing rapidly. Evidence from controlled laboratory studies demonstrates that nocturnal light exposure can strain the visual system, disrupt circadian physiology, suppress melatonin secretion, and impair sleep. There is a growing body of work pointing to adverse effects of outdoor lighting on human health, including the risk of chronic diseases, but this knowledge is in a more nascent stage. In this Review, we synthesize recent research on the context-specific factors and physiology relevant to nocturnal light exposure in relation to human health and society, identify critical areas for future research, and highlight recent policy steps and recommendations for mitigating light pollution in the urban environment.

Science & Technology - Other Topics↗
DOE OSTI2020

Extremum seeking for optimal control problems with unknown time-varying systems and unknown objective functions

We consider the problem of optimal feedback control of an unknown, noisy, time-varying, dynamic system that is initialized repeatedly. Examples include a robotic manipulator which must perform the same motion, such as assisting a human, repeatedly and accelerating cavities in particle accelerators which are turned on for a fraction of a second with given initial conditions and vary slowly due to temperature fluctuations. In this paper, we present an approach that applies to systems of practical interest. The method presented here is model independent; does not require knowledge of the objective function; is robust to measurement noise; is applicable for any set of initial conditions; is applicable to simultaneously controlling an arbitrary number of parameters; and may be implemented with a broad range of continuous or discontinuous functions such as sine or square waves. For systems with convex cost functions we prove that our algorithm will produce controllers that approach the minimal cost. For linear systems we reproduce the cost minimizing linear quadratic regulator optimal controller that could have been designed analytically had the system and cost function been known. We demonstrate the effectiveness of the algorithm with simulation studies of noisy and time-varying systems.

42 ENGINEERING↗
DOE OSTI2024

Targeted protein degradation systems to enhance Wnt signaling

Molecules that facilitate targeted protein degradation (TPD) offer great promise as novel therapeutics. The human hepatic lectin asialoglycoprotein receptor (ASGR) is selectively expressed on hepatocytes. We have previously engineered an anti-ASGR1 antibody-mutant RSPO2 (RSPO2RA) fusion protein (called SWEETS) to drive tissue-specific degradation of ZNRF3/RNF43 E3 ubiquitin ligases, which achieved hepatocyte-specific enhanced Wnt signaling, proliferation, and restored liver function in mouse models, and an antibody–RSPO2RA fusion molecule is currently in human clinical trials. In the current study, we identified two new ASGR1- and ASGR1/2-specific antibodies, 8M24 and 8G8. High-resolution crystal structures of ASGR1:8M24 and ASGR2:8G8 complexes revealed that these antibodies bind to distinct epitopes on opposing sides of ASGR, away from the substrate-binding site. Both antibodies enhanced Wnt activity when assembled as SWEETS molecules with RSPO2RA through specific effects sequestering E3 ligases. In addition, 8M24-RSPO2RA and 8G8-RSPO2RA efficiently downregulate ASGR1 through TPD mechanisms. These results demonstrate the possibility of combining different therapeutic effects and degradation mechanisms in a single molecule.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Demonstration and Evaluation of the Human-Technology Integration Function Allocation Methodology

There is an imminent need for the existing nuclear power plants to reduce their operating and maintenance (O&M) costs to remain economically viable. Digital technology, including automation, provides a significant opportunity for the existing nuclear power plant fleet to transform the way in which work is accomplished, reducing O&M costs, and allowing the fleet to remain economically competitive. One notable opportunity to significantly reduce O&M costs pertains to modifications to the plant equipment and main control room (MCR). Existing instrumentation and control (I&C) technologies in the MCR are highly analog, costly to operate and maintain, and demand a high cognitive and physical workload from plant staff (i.e., operators). Digitalizing the MCR has a range of broad economic benefits, including improved plant performance and reduced manual work. Further, digital I&C systems can fundamentally change the way in which plant staff operate the plant; this is the concept of operation. Human-technology integration is important to ensure that impacts to the concept of operation are done in a way that account for capabilities of people and technology. Human-technology integration employs human factors engineering (HFE) methods and principles to maximize the benefits of digital technology, reducing human error, improving overall decision-making and usability. The U.S. Department of Energy Light Water Reactor Sustainability Program is applying human-technology integration research to ensure digital technologies are safe, reliable, and efficient. This paper documents the demonstration of the human-technology guidance developed by the Light Water Reactor Sustainability Program from a first-of-a-kind digital I&C upgrade, specifically addressing function analysis and allocation for a new digital I&C system that included changes in automation levels. The program’s specific approach is included in this work, following lessons learned. This document serves as a resource for industry to follow in applying human-technology integration and HFE to digital modifications, specific to function analysis and allocation. The lessons learned should be considered in the planning and execution of HFE activities that support such digital modifications.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Dissecting components of the Campylobacter jejuni fetMP-fetABCDEF gene cluster under iron limitation

Campylobacter jejuni is a leading cause of bacterial gastroenteritis worldwide. Acute infection can be an antecedent to highly debilitating long-term sequelae. The expression of iron acquisition systems is vital for C. jejuni to survive the low iron availability within the human gut. The C. jejuni fetMP-fetABCDEF gene cluster is known to be upregulated during human infection and under iron limitation. While FetM and FetP have been functionally linked to iron transport in prior work, here we assess the contribution of each of the downstream genes (fetABCDEF) to C. jejuni growth during both iron-depleted and iron-replete conditions. Significant growth impairment was observed upon disruption of fetA, fetB, fetC, and fetD, suggesting a role in FetMP-mediated iron acquisition for each encoded protein. FetA expression was not dependent on the presence of FetB, FetC, FetD, FetE, or FetF. The functions of the putative thioredoxins FetE and FetF were redundant under iron-limited growth, requiring a double deletion (ΔfetEF) to exhibit a growth defect. C. jejuni FetE was expressed, and the structure was solved to 1.50 Å, revealing structural similarity to thiol-disulfide oxidases. Functional characterization in biochemical assays showed that FetE reduced insulin at a slower rate than Escherichia coli Trx and that together, FetEF promoted substrate oxidation in cell extracts, suggesting that FetE (and presumably FetF) are oxidoreductases that can mediate oxidation in vivo. This study advances our understanding of the contributions of the fetMP-fetABCDEF gene cluster to virulence at a genetic and functional level, providing foundational knowledge toward mitigating C. jejuni-related morbidity and mortality.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

National User Resource for Biological Accelerator Mass Spectrometry (Final Report)

The National User Resource for Biological Accelerator Mass Spectrometry (User Resource) will provide isotopic analysis (primarily radiocarbon or 14C) by accelerator mass spectrometry (AMS) for NIH- funded researchers across the United States and will be the only User Resource of its type in the United States. The User Resource will provide measurement capability and expertise to a research community that requires highly sensitive, quantitative isotope analyses. Since commissioning a new accelerator mass spectrometer in June 2014, we have measured over 4000 samples a year for collaborators and service users. The User Resource will enable us to continue to meet these research needs, as well as provide for new users whose research programs would benefit from AMS as a measurement tool. The User Resource’s forte will be ultra-high sensitivity quantitation of radiocarbon and selected other radioisotopes for research studies where isotopes are required. Radioisotope labeling studies have been and will continue to be an important tool for addressing many complex biomedical science problems. AMS is a specialized and unique type of mass spectrometry that provides absolute quantitation of radiocarbon and other relevant radioisotopes with extreme sensitivity, having limits of detection in real samples on the order of a few attomol/mg of sample at measurement precisions of ~3%. It is the only instrumental method capable of quantifying radioisotope-labeled agents routinely in real-world samples with such precision and sensitivity. The sensitivity of AMS allows for the quantification of radiolabeled metabolites in extremely complex matrices of cells and organisms at very low concentrations and in small samples. AMS allows studies to be conducted without perturbing metabolism leading to more relevant quantification of metabolic rates and pathways. In addition, it enables quantification of pharmacokinetic and metabolic properties of toxicants at environmentally relevant concentrations in model systems as well as the ability to quantify pharmacokinetics and other molecular endpoints directly in humans. Such quantitative assessments can 1) improve risk assessment for toxicants, 2) address safety and efficacy considerations for therapeutic entities, 3) deepen understanding of xenobiotic and intermediary metabolism, 4) help understand the interactions between critical molecular pathways, and 5) improve efforts to model and predict various metabolic and biological states. These capabilities have been applied in a number of areas including research in carcinogenesis, toxicology, nutrition, pharmacology/drug development and basic biological science. As a NIGMS National Resource the National User Resource for Biological Accelerator Mass Spectrometry will help NIH funded scientists achieve a deeper understanding of the etiology of human health concerns by (1) enabling the quantification of pharmacokinetics and other molecular endpoints directly in humans; (2) offering the ability to conduct quantitative studies using biologics such as proteins or lipids, and thereby reducing the amount of radioisotope usage in biomedical labs; and (3) enabling more relevant studies of metabolic pathways in health and disease through the use of much lower, more biologically-relevant, concentrations of metabolic substrates in cells and intact organisms. Such studies support NIGMS’s basic biomedical research areas that contribute to the understanding of fundamental cellular and physiological principles and enable research supported by the Biophysics, Biomedical Technology, and Computational Biosciences (BBCB); Genetics and Molecular, Cellular, and Developmental Biology (GMCDB); Pharmacology, Physiology, Biological Chemistry (PPBC) and Training, Workforce Development, and Diversity (TWD) Divisions. Over the next five years, our goals are to: 1. Improve the efficiency of operation for AMS measurements through installation of new interfaces to our AMS systems, technical modifications to improve gas accepting ion source efficiency and upgrading our data analysis software for improved ease of use and data reporting. 2. Increase the accessibility and visibility of ultra-sensitive 14C measurements for the biomedical research community by training of new investigators and expanding our national user base. 3. Provide high throughput, ultra-sensitive 14C analysis for the NIGMS and NIH user community.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Broad-spectrum CRISPR-mediated inhibition of SARS-CoV-2 variants and endemic coronaviruses in vitro

A major challenge in coronavirus vaccination and treatment is to counteract rapid viral evolution and mutations. Here we demonstrate that CRISPR-Cas13d offers a broad-spectrum antiviral (BSA) to inhibit many SARS-CoV-2 variants and diverse human coronavirus strains with >99% reduction of the viral titer. We show that Cas13d-mediated coronavirus inhibition is dependent on the crRNA cellular spatial colocalization with Cas13d and target viral RNA. Cas13d can significantly enhance the therapeutic effects of diverse small molecule drugs against coronaviruses for prophylaxis or treatment purposes, and the best combination reduced viral titer by over four orders of magnitude. Using lipid nanoparticle-mediated RNA delivery, we demonstrate that the Cas13d system can effectively treat infection from multiple variants of coronavirus, including Omicron SARS-CoV-2, in human primary airway epithelium air-liquid interface (ALI) cultures. Our study establishes CRISPR-Cas13 as a BSA which is highly complementary to existing vaccination and antiviral treatment strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Integrate health into decision-making to foster climate action

The COVID-19 pandemic reveals that societies place a high value on healthy lives. Leveraging this momentum to establish a more central role for human health in the policy process will provide further impetus to a sustainable transformation of energy and food systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Demystifying Cyberattacks: Potential for Securing Energy Systems With Explainable AI : Preprint

Modernization of energy systems has led to in- creased interactions among multiple critical infrastructures and diverse stakeholders making the challenge of operational decision making more complex and at times beyond cognitive capabilities of human operators. The state-of-the-art machine learning and deep learning approaches show promise of supporting users with complex decision-making challenges, such as those occurring in our rapidly transforming cyber-physical energy systems. However, successful adoption of data-driven decision support technology for critical infrastructure will be dependent on the ability of these technologies to be trustworthy and contextually interpretable. In this paper, we investigate the feasibility of implementing XAI for interpretable detection of cyberattacks in the energy system. Leveraging a proof-of-concept simulation use case of detection of a data falsification attack on a photovoltaic system using XGBoost algorithm, we demonstrate how Local Interpretable Model-Agnostic Explanations (LIME), a flavor XAI approach, can help provide contextual and actionable interpretation of cyberattack detection.

artificial intelligence↗
DOE OSTI2022

Outage Cause Classification of Power Distribution Systems with Machine Learning and Real-World Data

Power distribution systems are geographically dispersed by nature. It may be affected by various factors, such as vegetation, weather, animal and human behaviors. Present response procedures to an outage event massively rely on expert experience and thus tend to be time-consuming. Automatic outage event detection and classification will help to reduce the responding and restoration time. However, this issue is less addressed with existing research done in this area. In this applied research, a set of waveform pre-processing techniques are first proposed to prepare the waveform data for being used as inputs to the classification algorithm. Further, a machine learning-based algorithm is proposed to classify the outage events according to their root causes, e.g. tree contact, animal contact, lightning, etc. Available data include three phase current & voltage waveforms and contextual information during the distribution system outages. The proposed machine learning algorithm takes the current and voltage waveforms as direct inputs in search of features that humans are unable to capture. Real data provided by a distribution company in the East Tennessee region is used to test the proposed pre-processing techniques and the classification algorithm.

Sun, Haoyuan↗