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

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Uncertainty quantification and sensitivity analysis of a nuclear thermal propulsion reactor startup sequence

The research presented in this article describes progress in applying stochastic methods, uncertainty quantification, parametric studies, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated via the radiation transport code Griffin to simulate neutronics. Our goal is to develop a reduced-order (surrogate) model that can be rapidly sampled with perturbations to multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums (CDs), which is itself controlled by a hybrid proportional-integral-derivative (PID) controller actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time [Λ] and effective delayed neutron fraction [ β eff ] from a transient Griffin simulation executed via Griffin’s improved quasi-static solver to provide the kinetic parameters) as inputs to functions that control the CD rotation angle. By investigating numerous stochastic approaches, we developed a dual-purpose surrogate model of the NTP system, using polynomial regression in the Multiphysics Object-Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM). The trained model can be rapidly sampled while simultaneously perturbing various input parameters, such as coefficients on the PID control or temperature (directly affecting the neutron cross section). The surrogate model delivers accurate (within 5%) results at speeds orders of magnitude faster (minutes, not days of computational time) than the base model. Once the surrogate model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs as well as the effects of these inputs on the model output. For example, coefficients used in the PID control system may vary due to some type of physical interference, or uncertainty may exist in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters, and operational boundaries can be determined. The goal of this work is to support development of an advanced control system for operating CDs in a functioning NTP system. This work is a scoping study of the MOOSE STM.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2021

Reoptimization of Quantum Circuits via Hierarchical Synthesis

The current phase of quantum computing is in the Noisy Intermediate-Scale Quantum (NISQ) era. On NISQ devices, two-qubit gates such as CNOTs are much noisier than single-qubit gates, so it is essential to minimize their count. Quantum circuit synthesis is a process of decomposing an arbitrary unitary into a sequence of quantum gates, and can be used as an optimization tool to produce shorter circuits to improve overall circuit fidelity. However, the time-to-solution of synthesis grows exponentially with the number of qubits. As a result, synthesis is intractable for circuits on a large qubit scale. In this paper, we propose a hierarchical, block-by-block opti-mization framework, QGo, for quantum circuit optimization. Our approach allows an exponential cost optimization to scale to large circuits. QGo uses a combination of partitioning and synthesis: 1) partition the circuit into a sequence of independent circuit blocks; 2) re-generate and optimize each block using quantum synthesis; and 3) re-compose the final circuit by stitching all the blocks together. We perform our analysis and show the fidelity improvements in three different regimes: small-size circuits on real devices, medium-size circuits on noisy simulations, and large-size circuits on analytical models. Our technique can be applied after existing optimizations to achieve higher circuit fidelity. Further, using a set of NISQ benchmarks, we show that QGo can reduce the number of CNOT gates by 29.9% on average and up to 50% when compared with industrial compiler optimizations such as t|ket). When executed on the IBM Athens system, shorter depth leads to higher circuit fidelity. We also demonstrate the scalability of our QGo technique to optimize circuits of 60+ qubits, Our technique is the first demonstration of successfully employing and scaling synthesis in the compilation tool chain for large circuits. Overall, our approach is robust for direct incorporation in production compiler toolchains to further improve the circuit fidelity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Identification Uncertainty in Inverse Material Model Parameter Determination: A Sensitivity‐Based Decision Process for Load Path Selection

This research proposes a sensitivity-based framework for selecting the optimal prescribed loading path for a biaxial cruciform specimen. Optimality here is determined by the direction and magnitude of the prescribed displacement that minimizes the influence of random noise on the material model parameter identification. Using simulated experimental data based on finite element simulation, in this work, we identify the material model parameters of a Ludwik hardening model and plane stress implementation of the Hill-48 yield criterion using finite element model updating (FEMU). Our analysis reveals that the identification (or estimator) uncertainty of model parameters depends on the displacement boundary conditions (i.e., loading sequence) and the ground-truth value of the individual parameters. Optimal experimental design (OED) criteria based on the Fisher information matrix were investigated to mitigate indecision in the choice of optimal load path when the identification uncertainty of different material model parameters optimized at different load paths. The determinant of the Fisher information matrix was chosen here as the more useful metric due to its ability to capture uncertainty of the most influential material model parameters. The proposed framework demonstrates potential for real-time automated load step selection using scalar criteria derived prior to mechanical loading. The framework can be generalized to other geometries, boundary conditions and material models, allowing this procedure to be utilized for different experimental configurations and materials.

Fayad, Samuel S. [University of Illinois at Urbana↗
DOE OSTI2024

The direct and indirect drivers shaping RNA viral communities in grassland soils

ABSTRACT Recent studies have revealed diverse RNA viral communities in soils. Yet, how environmental factors influence soil RNA viruses remains largely unknown. Here, we recovered RNA viral communities from bulk metatranscriptomes sequenced from grassland soils managed for 5 years under multiple environmental conditions including water content, plant presence, cultivar type, and soil depth. More than half of the unique RNA viral contigs (64.6%) were assigned with putative hosts. About 74.7% of these classified RNA viral contigs are known as eukaryotic RNA viruses suggesting eukaryotic RNA viruses may outnumber prokaryotic RNA viruses by nearly three times in this grassland. Of the identified eukaryotic RNA viruses and the associated eukaryotic species, the most dominant taxa were Mitoviridae with an average relative abundance of 72.4%, and their natural hosts, Fungi with an average relative abundance of 56.6%. Network analysis and structural equation modeling support that soil water content, plant presence, and type of cultivar individually demonstrate a significant positive impact on eukaryotic RNA viral richness directly as well as indirectly on eukaryotic RNA viral abundance via influencing the co-existing eukaryotic members. A significant negative influence of soil depth on soil eukaryotic richness and abundance indirectly impacts soil eukaryotic RNA viral communities. These results provide new insights into the collective influence of multiple environmental and community factors that shape soil RNA viral communities and offer a structured perspective of how RNA virus diversity and ecology respond to environmental changes. IMPORTANCE Climate change has been reshaping the soil environment as well as the residing microbiome. This study provides field-relevant information on how environmental and community factors collectively shape soil RNA communities and contribute to ecological understanding of RNA viral survival under various environmental conditions and virus-host interactions in soil. This knowledge is critical for predicting the viral responses to climate change and the potential emergence of biothreats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Online Learning and Pricing for Network Revenue Management with Reusable Resources

We consider a price-based network revenue management problem with multiple products and multiple reusable resources. Each randomly arriving customer requests a product (service) that needs to occupy a sequence of reusable resources (servers). We adopt an incomplete information setting where the firm does not know the price-demand function for each product and the goal is to dynamically set prices of all products to maximize the total expected revenue of serving customers. We propose novel batched bandit learning algorithms for finding near-optimal pricing policies, and show that they admit a near-optimal cumulative regret bound of $O(J\sqrt{XT})$, where J, X, and T, are the numbers of products, candidate prices, and service periods, respectively. As part of our regret analysis, we develop the first finite-time mixing time analysis of an open network queueing system (i.e., the celebrated Jackson Network), which could be of independent interest. Our numerical studies show that the proposed approaches perform consistently well.

42 ENGINEERING↗
DOE OSTI2021

The Hyperthermophilic Restriction-Modification Systems of Thermococcus kodakarensis Protect Genome Integrity

Thermococcus kodakarensis (T. kodakarensis), a hyperthermophilic, genetically accessible model archaeon, encodes two putative restriction modification (R-M) defense systems, TkoI and TkoII. TkoI is encoded by TK1460 while TkoII is encoded by TK1158. Bioinformative analysis suggests both R-M enzymes are large, fused methyltransferase (MTase)-endonuclease polypeptides that contain both restriction endonuclease (REase) activity to degrade foreign invading DNA and MTase activity to methylate host genomic DNA at specific recognition sites. In this work, we demonsrate T. kodakarensis strains deleted for either or both R-M enzymes grow more slowly but display significantly increased competency compared to strains with intact R-M systems, suggesting that both TkoI and TkoII assist in maintenance of genomic integrity in vivo and likely protect against viral- or plasmid-based DNA transfers. Pacific Biosciences single molecule real-time (SMRT) sequencing of T. kodakarensis strains containing both, one or neither R-M systems permitted assignment of the recognition sites for TkoI and TkoII and demonstrated that both R-M enzymes are TypeIIL; TkoI and TkoII methylate the N 6 position of adenine on one strand of the recognition sequences GTGAAG and TTCAAG, respectively. Further in vitro biochemical characterization of the REase activities reveal TkoI and TkoII cleave the DNA backbone GTGAAG(N) 20 /(N) 18 and TTCAAG(N) 10 /(N) 8 , respectively, away from the recognition sequences, while in vitro characterization of the MTase activities reveal transfer of tritiated S-adenosyl methionine by TkoI and TkoII to their respective recognition sites. Together these results demonstrate TkoI and TkoII restriction systems are important for protecting T. kodakarensis genome integrity from invading foreign DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

New Determination of Fundamental Properties of Palomar 5 Using Deep DESI Imaging Data

The legacy imaging surveys for the Dark Energy Spectroscopic Instrument project provides multiple-color photometric data, which are about 2 mag deeper than those from the SDSS. In this study, we redetermine the fundamental properties for an old halo globular cluster of Palomar 5 based on these new imaging data, including structure parameters, stellar population parameters, and luminosity and mass functions. These characteristics, together with its tidal tails, are key for dynamical studies of the cluster and constraining the mass model of the Milky Way. By fitting the King model to the radial surface density profile of Palomar 5, we derive the core radius of [[Formula]], tidal radius of [[Formula]], and concentration parameter of c = 0.78 ± 0.04. We apply a Bayesian analysis method to derive the stellar population properties and get an age of 11.508 ± 0.027 Gyr, metallicity of [Fe/H] = −1.798 ± 0.014, reddening of E(B − V) = 0.0552 ± 0.0005, and distance modulus of (m−M){sub 0} = 16.835±0.006. The main-sequence luminosity and mass functions for both the cluster center and tidal tails are investigated. The luminosity and mass functions at different distances from the cluster center suggest that there is obvious spatial mass segregation. Many faint low-mass stars have been evaporated at the cluster center, and the tidal tails are enhanced by low-mass stars. Both the concentration and relaxation times suggest that Palomar 5 is a totally relaxed system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Sex- and age-specific aspects of human peripheral T-cell dynamics

Background: The diversity of the antigenic T cell receptor (TCR) repertoire clonally expressed on T lymphocytes is a key element of the adaptive immune system protective functions. A decline in diversity in the older adults is associated with health deterioration. This diversity is generated by the rearrangement of TRB genes coding for TCR chains during lymphocyte differentiation in the thymus, but is essentially maintained by peripheral T lymphocytes proliferation for most of life. Deep sequencing of rearranged TRB genes from blood cells allows the monitoring of peripheral T cell repertoire dynamics. We analysed two aspects of rearranged TRB diversity, related to T lymphocyte proliferation and to the distribution of the T cell clone size, in a collection of repertoires obtained from 1 to 74 years-old donors. Results: Our results show that peripheral T lymphocytes expansion differs according to the recombination status of their TRB loci. Their proliferation rate changes with age, with different patterns in men and women. T cell clone size becomes more heterogeneous with time, and, in adults, is always more even in women. Importantly, a longitudinal analysis of TRB repertoires obtained at ten years intervals from individual men and women confirms the findings of this cross-sectional study. Conclusions: Peripheral T lymphocyte proliferation partially depends on their thymic developmental history. The rate of proliferation of T cells differing in their TRB rearrangement status is different in men and women before the age of 18 years old, but similar thereafter.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The gMOSS: the galaxy survey and galaxy populations of the large homogeneous field

ABSTRACT We present the gMOSS (Galaxies of Medium-band One-meter Schmidt telescope Survey) catalogue of ∼19 000 galaxies in 20 filters (4 broad-band SDSS and 16 medium-band filters). We observed 2.386 deg2 on the central part of the HS47.5-22 field with the 1-m Schmidt telescope of the Byurakan Astrophysical Observatory. The gMOSS is a complete flux-limited sample of galaxies with a threshold magnitude of r SDSS ≤ 22.5 AB. From photometric measurements with 16 medium-band filters and u SDSS, we get spectral energy distributions for each object in the field, which are used for further analysis. Galaxy classification and photometric redshift estimation based on spectral template matching with zebra software. The obtained redshift accuracy is σNMAD < 0.0043. Using the SED-fitting cigale code, we obtained the main properties of the stellar population of galaxies, such as rest-frame (u − r)res colour, stellar mass, extinction, and mass-weighted age with a precision of 0.16 ± 0.07 mag, 0.14 ± 0.04 dex, 0.27 ± 0.1 mag, and 0.08 ± 0.04 dex, respectively. Using a dust-corrected colour–mass diagram, we divided the full sample into populations of red and blue galaxies and considered the dependencies between stellar mass and age. Throughout cosmic time, red sequence galaxies remain older and more massive than blue cloud galaxies. The star formation history of a complete subsample of galaxies selected in the redshift range 0.05 ≤ z ≤ 0.015 with <$\mathrm{log} M \mathrm{\gt }_\mathrm{[M_\odot ]}$>8.3 shows an increase in the SFRD up to z ∼ 3, under the results obtained in earlier studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Safety Benefits Assessment for Accident Tolerant Fuels in Consideration of Steam Generator Tube Degradation Using Dynamic Event Tree Analysis

Accident tolerant fuel (ATF) is expected to delay or prevent core damage by providing additional coping time under accidents involving loss of core cooling. The effect of extended coping time may vary depending on the plant response to accidents. Age-related component degradation that deteriorates plant performance over time could have an impact on the actual advantages of ATF. The potential safety benefits of two near-term ATF candidates, including Cr-coated Zr cladding and FeCrAl cladding, are assessed for a 2-in. loss-of-coolant accident with failed high-pressure safety injection using the dynamic event tree (DET) approach considering possible stress corrosion cracking of steam generator (SG) tubing under aging. The DET approach allows likelihood quantification of accident sequences leading to core damage, including stochastic variation of system response and human actions during accident mitigation. The safety benefits of the selected ATF claddings in terms of additional coping time and the core damage frequency reduction rate under specified accident situations were quantitatively estimated. The results show that the deployment of the two selected ATF claddings is expected to lead to longer coping times and lower core damage frequency due to the wider safety margin to peak cladding temperature they provide. The safety advantages would be greater as SG tube degradation proceeds. Thus, the two ATF candidates would lead to less severe consequences in terms of likelihood of core damage and susceptibility to the SG tube degradation than UO 2 -Zr fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes

The design of materials for electrochemical energy conversion is complicated by a vast search space of candidate materials and multifaceted property requirements: multicarrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Although self-driving laboratories are rapidly rising to address such material optimization problems, the required infrastructure for integrated, large-scale robotic facilities can be cost-prohibitive. Here we develop and evaluate a closed-loop measurement system for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers, building on top of an existing benchtop instrument and integrating techniques for rapid impedance measurement and automated analysis. This system exemplifies a “minimum viable” self-driving implementation that can deliver substantial benefits with relatively simple infrastructure. Combinatorial thin-film microelectrode libraries are characterized with a recently developed joint time-domain and frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed an active learning and Bayesian optimization process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces the screening time by tenfold with optimized experimental sequences. We apply this system to Ba⁡(Co,Fe,Zr,Y)⁢O 3−𝛿 combinatorial libraries and evaluate its effectiveness for learning material property trends and optimizing expensive-to-evaluate properties such as activation energy. This offers insights into key methodological aspects of practical autonomous experimentation, including surrogate model validation, cost-aware acquisition functions, and high-throughput data interpretation. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight real-world experimental challenges of thin-film degradation and numerical instability in surrogate models.

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

Spatiotemporal analysis identifies ABF2 and ABF3 as key hubs of endodermal response to nitrate

Nitrate is a nutrient and a potent signal that impacts global gene expression in plants. However, the regulatory factors controlling temporal and cell type–specific nitrate responses remain largely unknown. We assayed nitrate-responsive transcriptome changes in five major root cell types of the Arabidopsis thaliana root as a function of time. We found that gene-expression response to nitrate is dynamic and highly localized and predicted cell type–specific transcription factor (TF)–target interactions. Among cell types, the endodermis stands out as having the largest and most connected nitrate-regulatory gene network. ABF2 and ABF3 are major hubs for transcriptional responses in the endodermis cell layer. We experimentally validated TF–target interactions for ABF2 and ABF3 by chromatin immunoprecipitation followed by sequencing and a cell-based system to detect TF regulation genome-wide. Validated targets of ABF2 and ABF3 account for more than 50% of the nitrate-responsive transcriptome in the endodermis. Moreover, ABF2 and ABF3 are involved in nitrate-induced lateral root growth. Our approach offers an unprecedented spatiotemporal resolution of the root response to nitrate and identifies important components of cell-specific gene regulatory networks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Techno-economic analysis of the use of atomic layer deposited transition metal oxides in silicon heterojunction solar cells

The industry for producing silicon solar cells and modules has grown remarkably over the past decades, with more than a 100-fold reduction in price over the past 45?years. The main solar cell fabrication technology has shifted over that time and is currently dominated by the passivated emitter and rear cell (PERC). Other technologies are expected to increase in market share, including tunnel-oxide passivated contact (TOPCon) and heterojunction technology (HJT). In this paper, we examine the cost potential for using atomic layer deposition (ALD) to form transition metal oxide (TMO) layers (MoO x , TiO x and aluminium-doped zinc oxide [AZO]) to use as lower cost alternatives of the p-doped, n-doped and indium tin oxide (ITO) layers, respectively, the layers normally used in HJT solar cells. Using a bottom-up cost and uncertainty model with equipment cost data and process experience in the lab, we find that the production cost of these variations will likely be lower per wafer than standard HJT, with the main cost drivers being the cost of the ALD precursors at high-volume production. We then considered what efficiency is required for these sequences to be cost effective in $/W and discuss whether these targets are technically feasible. This work motivates further work in developing these ALD TMO processes to increase their efficiency towards their theoretical limits to take advantage of the processing cost advantage.

14 SOLAR ENERGY↗
DOE OSTI2025

From subsidies to stressors: Positively skewed ecological gradients alter biological responses to nutrients in streams

Abstract Subsidy–stress gradients offer a useful framework for understanding ecological responses to perturbation and may help inform ecological metrics in highly modified systems. Historic, region‐wide shifts from bottomland hardwood forest to row crop agriculture can cause positively skewed impact gradients in alluvial plain ecoregions, resulting in tolerant organisms that typically exhibit a subsidy response (increased abundance in response to environmental stressors) shifting to a stress response (declining abundance at higher concentrations). As a result, observed biological tolerance in modified ecosystems may differ from less modified regions, creating significant challenges for detecting biological responses to restoration efforts. Using the agriculturally dominated Mississippi Alluvial Plain (MAP) ecoregion in Mississippi, USA, as a case study, we tested the hypothesis that macroinvertebrate taxa that typically display a subsidy response to nutrient enrichment in less modified ecoregions (i.e., nutrient‐tolerance) shift to a stress response to increasing nutrients in highly modified watersheds with elevated baseline nutrient conditions (i.e., nutrient intolerance). The abundance and diversity of MAP‐specific intolerant taxa identified with threshold indicator taxa analysis were either unresponsive or exhibited a subsidy response to increasing nutrients in less modified ecoregions in Mississippi with less land alteration and lower nutrient concentrations, but declined at higher concentrations, providing evidence for a stress response to elevated nutrients in the MAP. Additionally, MAP‐specific tolerant and intolerant taxa richness responded to increased nutrients predictably and consistently across space and time within the MAP. However, in MAP streams, elevated specific conductance was predicted to dampen the response of tolerant and intolerant taxa richness to increasing nutrient concentrations, highlighting the importance of considering multistressor interactions when interpreting biological data. Lastly, we demonstrate the efficacy of this approach with sediment bacterial communities characterized with amplicon sequencing, which lack sufficient life history characteristics necessary for the development of multimetric indices. Both macroinvertebrate and bacterial communities responded similarly to increasing nutrient concentrations, suggesting DNA‐based approaches may provide an efficient biological assessment tool for monitoring water quality improvements in highly modified watersheds.

DeVilbiss, Stephen E. [U.S. Geological Survey Lowe↗
DOE OSTI2021

Comparative genomic and phenotypic characterization of invasive non-typhoidal Salmonella isolates from Siaya, Kenya

Non-typhoidal Salmonella (NTS) is a major global health concern that often causes bloodstream infections in areas of the world affected by malnutrition and comorbidities such as HIV and malaria. Developing a strategy to control the emergence and spread of highly invasive and antimicrobial resistant NTS isolates requires a comprehensive analysis of epidemiological factors and molecular pathogenesis. Here, we characterize 11 NTS isolates that caused bloodstream infections in pediatric patients in Siaya, Kenya from 2003–2010. Nine isolates were identified as S . Typhimurium sequence type 313 while the other two were S . Enteritidis. Comprehensive genotypic and phenotypic analyses were performed to compare these isolates to those previously identified in sub-Saharan Africa. We identified a S . Typhimurium isolate referred to as UGA14 that displayed novel plasmid, pseudogene and resistance features as compared to other isolates reported from Africa. Notably, UGA14 is able to ferment both lactose and sucrose due to the acquisition of insertion elements on the pKST313 plasmid. These findings show for the first time the co-evolution of plasmid-mediated lactose and sucrose metabolism along with cephalosporin resistance in NTS further elucidating the evolutionary mechanisms of invasive NTS phenotypes. These results further support the use of combined genomic and phenotypic approaches to detect and characterize atypical NTS isolates in order to advance biosurveillance efforts that inform countermeasures aimed at controlling invasive and antimicrobial resistant NTS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Precursor Analysis Report: Cyber Attack on Thyssenkrupp Blast Furnace 2014

The Cyber Attack on Thyssenkrupp Blast Furnace 2014 Precursor Analysis Report leverages publicly available information about the Thyssenkrupp Steel Mill 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. In December 2014, the German Government’s Federal Office for Information Security (BSI) released a report detailing a cyber attack on a German steel mill that occurred earlier that year, though exact dates and details of the attack were not revealed. While the report did not specify the name of the company, multiple sources identified the victim as one of Europe’s largest steel manufacturers, Thyssenkrupp AG. Further, Thyssenkrupp announced on 16 May of that year that Europe’s largest blast furnace, “Schwelgern 2,” located at its facility in Duisburg, Germany, would be offline for several weeks for repairs and upgrades, suggesting Schwelgern 2 was likely the target of the attack. The attack began in early 2014, when adversaries infiltrated the victim steel mill’s Information Technology (IT) network via a spearphishing campaign, then worked their way into the Operational Technology (OT) environment, where they executed software that caused denial of service, denial of control, and eventually a loss of control. This led to the blast furnace shutting down without proper safety procedures, resulting in catastrophic physical damage. No lives were lost in the incident, but ThyssenKrupp suffered $4 million in damage to the blast furnace and an additional $6 million in lost revenue. The adversaries required specialized knowledge and expertise in steel production, which enabled them to compromise a variety of internal systems and components across both IT and OT networks. The attack also demonstrated detailed knowledge of the industrial control systems (ICS) and production processes being used. This combination resulted in one of the earliest known publicly reported cybersecurity incidents resulting in physical damage to ICS equipment. Researchers and analysts identified 19 unique techniques (used in a sequence of 20 steps) utilized during the attack with a total of 454 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. Fifteen of the identified techniques used during the Thyssenkrupp cyber attack were precursors to the triggering event. Analysis identified 369 observables associated with these precursor techniques, 316 of which were assessed to have an increased likelihood of being perceived in the 120 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↗
DOE OSTI2023

Precursor Analysis Report: JBS Foods Ransomware Attack 2021

The JBS Foods 2021 Ransomware Attack Precursor Analysis Report leverages publicly available information about the JBS ransomware 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. In late May 2021, one of the world’s largest meat producers, JBS Foods, announced they had fallen victim to a worldwide ransomware attack, later found to be REvil ransomware. In the United States alone, JBS Foods accounts for nearly 25% of beef and roughly 20% of pork production. Adversaries initially launched a Distributed Denial of Service (DDoS) attack on the company’s Information Technology (IT) networks in Australia, but the attack impacted operations in Brazil, Canada, and the United States, as well. The attack caused plant operations in all four countries to shut down for at least one day. All nine of the U.S. meatpacking plants temporarily shut down because of the attack. The adversaries initially demanded a $\$$22 million ransom for the company’s data, but later negotiated the ransom down to $\$$11 million even after JBS Foods restored most of their systems. JBS Foods eventually paid the $\$$11 Million for reassurance from the adversaries that none of their customers’ data would be compromised in the future. Despite its short duration, the attack still caused large stocks of meat to spoil. The incident also underscored how adversaries can simultaneously compromise and move laterally through global subsidiaries of an organization. Researchers and analysts identified 22 unique techniques (in a sequence of 21 steps) utilized during the attack with a total of 361 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. Sixteen of the identified techniques used during the JBS Foods cyber attack were precursors to the triggering event. Analysis identified 308 observables associated with these precursor techniques, 163 of which were assessed to have an increased likelihood of being perceived in the 75 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↗
DOE OSTI2023

Precursor Analysis Report: Industroyer2 and Wiper Malware Targeting Ukrainian Energy Provider 2022

The Industroyer2 and Wiper Malware Targeting Ukrainian Energy Provider 2022 Precursor Analysis Report leverages publicly available information about the Industroyer2 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. An adversary attempted to cause a blackout in Ukraine in April 2022 by using the Industroyer2 malware against a regional Ukrainian energy provider. The adversary targeted eight high-voltage electrical substations and utilized the malware in tandem with disk wipers for Windows, Linux, and Solaris operating systems in an attempt to make response and recovery efforts more difficult. The adversary reused a piece of the original Industroyer malware designed to open circuit breakers and de-energize target substations. The adversary gained initial access to the victim’s enterprise network through unknown means in February 2022 and was able to perform reconnaissance, pivot to the operations network, and reside in the system for at least 51 days. This gave the adversary a detailed understanding of the environment and allowed them to customize the Industroyer2 malware to the victim’s operations network. However, defenders detected and stopped the attack before the adversary could achieve their intended impact. Had the Industroyer2 attack been successful, it could have caused a blackout for more than two million people during the early stages of Russia’s invasion of Ukraine. Researchers and analysts identified 22 unique techniques (used in a sequence of 31 steps) utilized during the attack with a total of 297 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. Twenty-three of the identified techniques used during the Industroyer2 cyber attack were precursors to the triggering event. Analysis identified 224 observables associated with these precursor techniques, 122 of which were assessed to have an increased likelihood of being perceived in the 51 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↗