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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Constraints on the Progenitor of SN 2010jl and Pre-existing Hot Dust in its Surrounding Medium

A search for the progenitor of SN 2010jl, an unusually luminous core-collapse supernova of Type IIn, using pre-explosion Hubble/WFPC2 and Spitzer/IRAC images of the region, yielded upper limits on the UV and near-infrared (IR) fluxes from any candidate star. These upper limits constrain the luminosity and effective temperature of the progenitor, the mass of any pre-existing dust in its surrounding circumstellar medium (CSM), and dust proximity to the star. A lower limit on the CSM dust mass is required to hide a luminous progenitor from detection by Hubble. Upper limits on the CSM dust mass and constraints on its proximity to the star are set by requiring that the absorbed and reradiated IR emission not exceed the IRAC upper limits. Using the combined extinction-IR emission constraints, we present viable M{sub d}--R{sub 1} combinations, where M {sub d} and R {sub 1} are the CSM dust mass and its inner radius. These depend on the CSM outer radius, dust composition and grain size, and the properties of the progenitor. The results constrain the pre-supernova evolution of the progenitor, and the nature and origin of the observed post-explosion IR emission from SN 2010jl. In particular, an η Car-type progenitor will require at least 4 mag of visual extinction to avoid detection by Hubble. This can be achieved with dust masses ≳10{sup −3} M{sub ⊙} (less than the estimated 0.2–0.5 M{sub ⊙} around η Car), which must be located at distances of ≳10{sup 16} cm from the star to avoid detection by Spitzer.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Optimal Attack Strategies Subject to Detection Constraints Against Cyber-Physical Systems

This paper studies an attacker against a cyberphysical system (CPS) whose goal is to move the state of a CPS to a target state while ensuring that his or her probability of being detected does not exceed a given bound. The attacker’s probability of being detected is related to the nonnegative bias induced by his or her attack on the CPS’s detection statistic. We formulate a linear quadratic cost function that captures the attacker’s control goal and establish constraints on the induced bias that reflect the attacker’s detection-avoidance objectives. When the attacker is constrained to be detected at the false-alarm rate of the detector, we show that the optimal attack strategy reduces to a linear feedback of the attacker’s state estimate. In the case that the attacker’s bias is upper bounded by a positive constant, we provide two algorithms – an optimal algorithm and a sub-optimal, less computationally intensive algorithm – to find suitable attack sequences. Lastly, we illustrate our attack strategies in numerical examples based on a remotely-controlled helicopter under attack.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

All About PID - Testing and Avoidance in the Field

Potential-induced degradation can cause significant power loss in modules if the appropriate precautions are not taken. In the first part of a new series in PV Tech Power on module failure, Peter Hacke and Steve Johnston assess the current state-of-the-art in detecting, avoiding and mitigating the worst effects of PID.

14 SOLAR ENERGY↗
DOE OSTI2017

Cyber-Physical Attacks With Control Objectives

This study studies attackers with control objectives against cyber-physical systems (CPSs). The goal of the attacker is to counteract the CPS's controller and move the system to a target state while evading detection. We formulate a cost function that reflects the attacker's goals, and, using dynamic programming, we show that the optimal attack strategy reduces to a linear feedback of the attacker's state estimate. By changing the parameters of the cost function, we show how an attacker can design optimal attacks to balance the control objective and the detection avoidance objective. In conclusion, we provide a numerical illustration based on a remotely controlled helicopter under attack.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Adaptive Threshold-Based Zonal Isolation of Faults in a Multiterminal DC Using Local Measurements

Fast and accurate methods of fault detection and isolation are a pre-emptive measure in multiterminal dc (MTdc) systems. Zonal isolation of faults is necessary to prevent any misopertation of the dc breakers that can lead to a shutdown of the network. Existing techniques require fast-communication or data synchronization methods have their own disadvantages. This article proposes a method for efficient fault zone isolation without the need of a communication link that prevents any misoperation of the dc breakers in a radial MTdc. This method provides individual local measurement-based control to the hybrid dc circuit breakers (dcCB). Faults created outside the zone of protection for a breaker create a change in the rate of change of current or voltage leading to misoperation. To avoid detection using a fixed threshold, an adaptive threshold based approach is suggested that updates the threshold based on the present operating status. Sensitivity analysis by varying the current limiting inductance and fault location is performed. In conclusion, a three terminal radial model of an MTdc is used for zonal isolation using power system computer aided design/electromagnetic transients including dc.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

APT malware static trace analysis through bigrams and graph edit distance

Research and business organizations are vulnerable to attack by malware, particularly advanced persistent threat malware tailored for a specific target. Malware identification is made more difficult because samples can be subtly altered to avoid detection by methods that check for an identical match to known code. Different versions of an original piece of malware form a malware family. And when new malicious software is identified, reverse engineers seek to identify its origin and purpose. Knowing whether new malware is from a known family or a previously unobserved family aids the efficiency of reverse engineers. Furthermore, this article presents a three-stage method to classify new malware into a family by comparing its similarity to existing static traces, and assigning it to the most similar family. First, a fast filtering method creates a shortlist of samples with some similarity to the new malware, using a simple bigram comparison of the instructions. The second stage takes the call graph view of the shortlisted static traces and uses simulated annealing to estimate the graph edit distance, a measure of dissimilarity between graphs. Finally, a random forest classifier combines the previous two results to predict the family to which a new sample belongs. Our paper also considers how to detect when malware is from a new family.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Collaboration and Negotiation

Collaboration and Negotiation is a critical high-level function of an Autonomous Intelligent Cyber-Defense Agent (AICA) that enables communication among agents, central cyber C2, and human operators. Maintaining the Confidentiality, Integrity, and Availability (CIA) triad while achieving mission goals requires stealthy AICA agents to exercise: 1) minimal communication as needed for avoiding detection, 2) verification of information received with possibly limited resources, and 3) active learning during operations to address dynamic conditions. Moreover, negotiations to jointly identify and execute a Course of Action (COA) solution will require building consensus under distributed and/or decentralized multiagent settings with information uncertainties. This chapter presents algorithmic approaches for enabling the collaboration and negotiation function. Strengths and limitations of potential techniques are identified, and a representative example is illustrated. Recommendations for future development are also discussed.

Chatterjee, Samrat↗
DOE OSTI2013

Th1-skewed tissue responses to a mycolyl glycolipid in mycobacteria-infected rhesus macaques

Highlights: •Glucose monomycolate (GMM) is a marker glycolipid for active tuberculosis. •Tissue responses to GMM involved up-regulation of Th1-attracting chemokines. •Th1-skewed local responses were mounted at the GMM-injected tissue. -- Abstract: Trehalose 6,6′-dimycolate (TDM) is a major glycolipid of the cell wall of mycobacteria with remarkable adjuvant functions. To avoid detection by the host innate immune system, invading mycobacteria down-regulate the expression of TDM by utilizing host-derived glucose as a competitive substrate for their mycolyltransferases; however, this enzymatic reaction results in the concomitant biosynthesis of glucose monomycolate (GMM) which is recognized by the acquired immune system. GMM-specific, CD1-restricted T cell responses have been detected in the peripheral blood of infected human subjects and monkeys as well as in secondary lymphoid organs of small animals, such as guinea pigs and human CD1-transgenic mice. Nevertheless, it remains to be determined how tissues respond at the site where GMM is produced. Here we found that rhesus macaques vaccinated with Mycobacterium bovis bacillus Calmette–Guerin mounted a chemokine response in GMM-challenged skin that was favorable for recruiting T helper (Th)1 T cells. Indeed, the expression of interferon-γ, but not Th2 or Th17 cytokines, was prominent in the GMM-injected tissue. The GMM-elicited tissue response was also associated with the expression of monocyte/macrophage-attracting CC chemokines, such as CCL2, CCL4 and CCL8. Furthermore, the skin response to GMM involved the up-regulated expression of granulysin and perforin. Given that GMM is produced primarily by pathogenic mycobacteria proliferating within the host, the Th1-skewed tissue response to GMM may function efficiently at the site of infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Sensor and Actuator Attacks on Hierarchical Control Systems with Domain-Aware Operator Theory

Cyber-Physical Systems (CPSs) provide opportunities for cyber attacks to have physical impacts. Advanced Persistent Threats (APTs) are a subclass of cyber threats that act stealthily to avoid detection and enable long-term attacks. Here, we build on our past work in APT modelling to combine deception-based sensor bias attacks and direct actuator manipulations in attacks against a hierarchical control system. That past work used the Koopman operator to develop a data-driven, domain-aware, optimization-based attacker model. Using an expansion of this model, we compute several different attacks, including multiple simultaneous attacks, against a high-fidelity commercial building emulator and compare the impacts of those attacks to each other. One next step of interest is to construct a defender system, built on the same modelling approach, designed to detect and mitigate such attacks.

koopman operator, Cyber-Physical Security, machine↗
DOE OSTI2020

Relative reproductive phenology and synchrony affect neonate survival in a nonprecocial ungulate

Abstract Degree of reproductive synchronization in prey is hypothesized as a predator defense strategy reducing prey risk via predator satiation or predator avoidance. Species with precocial young, especially those exposed to specialist predators, should be highly synchronous to satiate predators (predator satiation hypothesis), while prey with nonprecocial (i.e. altricial) young, especially those exposed to generalist predators, should become relatively asynchronous to avoid predator detection (predator avoidance hypothesis). The white‐tailed deer Odocoileus virginianus in North America is an example of a nonprecocial ungulate that uses the hider strategy early in life; its primary predator (coyote; Canis latrans ) is a generalist, making white‐tailed deer a good model species to test the predator avoidance hypothesis. We used birth dates and known fates of white‐tailed deer neonates ( n = 1,032) across nine study sites varying in relative synchrony and predator assemblages to test the predator avoidance hypothesis. We predicted that relative birthing asynchrony of the population would increase relative survival at the population level; therefore, at the individual scale, neonate birth date nearer to mean birthing date in a respective population would not influence individual survival. Coyotes were responsible for the majority of predation events, and survival of those neonates increased the closer the individual was born to peak birthing season in each respective population. Also, at the population level, reproductive asynchronization negatively affected survival. Contrary to the predator avoidance hypothesis, our data indicate patterns in neonate survival for white‐tailed deer better support the predator satiation hypothesis at the individual and population level. Additionally, coyotes may present a selective force great enough to shift reproductive synchrony such that predator satiation may become a feasible defense strategy for neonates at local spatial scales. Our results indicate that synchronizing reproduction may still be the most effective strategy to reduce individual predation risk from generalist predators, particularly when the window of heightened resource availability to the prey is narrow. A free Plain Language Summary can be found within the Supporting Information of this article.

Michel, Eric S.↗
DOE OSTI2016

The genome of the emerging barley pathogen Ramularia collo-cygni

Ramularia collo-cygni is a newly important, foliar fungal pathogen of barley that causes the disease Ramularia leaf spot. The fungus exhibits a prolonged endophytic growth stage before switching life habit to become an aggressive, necrotrophic pathogen that causes significant losses to green leaf area and hence grain yield and quality. The R. collo-cygni genome was sequenced using a combination of Illumina and Roche 454 technologies. The draft assembly of 30.3 Mb contained 11,617 predicted gene models. Our phylogenomic analysis confirmed the classification of this ascomycete fungus within the family Mycosphaerellaceae, order Capnodiales of the class Dothideomycetes. A predicted secretome comprising 1053 proteins included redoxrelated enzymes and carbohydrate-modifying enzymes and proteases. The relative paucity of plant cell wall degrading enzyme genes may be associated with the stealth pathogenesis characteristic of plant pathogens from the Mycosphaerellaceae. A large number of genes associated with secondary metabolite production, including homologs of toxin biosynthesis genes found in other Dothideomycete plant pathogens, were identified. The genome sequence of R. collo-cygni provides a framework for understanding the genetic basis of pathogenesis in this important emerging pathogen. The reduced complement of carbohydrate-degrading enzyme genes is likely to reflect a strategy to avoid detection by host defences during its prolonged asymptomatic growth. Of particular interest will be the analysis of R. collo-cygni gene expression during interactions with the host barley, to understand what triggers this fungus to switch from being a benign endophyte to an aggressive necrotroph.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Fault Resilient Domain Decomposition Preconditioner for PDEs

The move towards extreme-scale computing platforms challenges scientific simulations in many ways. Given the recent tendencies in computer architecture development, one needs to reformulate legacy codes in order to cope with large amounts of communication, system faults and requirements of low-memory usage per core. In this work, we develop a novel framework for solving partial differential equations (PDEs) via domain decomposition that reformulates the solution as a state-of-knowledge with a probabilistic interpretation. Such reformulation allows resiliency with respect to potential faults without having to apply fault detection, avoids unnecessary communication and is generally well-positioned for rigorous uncertainty quantification studies that target improvements of predictive fidelity of scientific models. We demonstrate our algorithm for one-dimensional PDE examples where artificial faults have been implemented as bit-flips in the binary representation of subdomain solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Assessing the Effectiveness of Generalized Likelihood Ratio Test Detector Schemes in Seismic Event Detection and the Avoidance of Nontarget Signals

Cross-correlation techniques have played a long-standing and pivotal role in seismic event monitoring. However, the performance of correlation-based detectors is challenged by nuisance seismicity, or nontarget signals. Such detections are a problem when the mission is to automatically map events to the correct source region. Using aftershocks of the 2014 $M_w$ 6.0 South Napa, California, earthquake, we demonstrate the effectiveness of utilizing a dynamic correlation processor framework in a generalized likelihood ratio test (GLRT) detector configuration to minimize nontarget detections. A GLRT maximizes a detection statistic with respect to one or more unknown parameters. In this case, the detection statistic is a template signal match against the waveform in a window sliding over a data stream, and the unknown parameter is an index variable indicating group membership of the template event or events. Detected events are assigned to the event group that yields the largest detection statistic. In this work, our results show that a GLRT detector will outperform a suite of independently operating correlation and subspace detectors in terms of having a lower nontarget detection rate at a given missed detection rate. We also show that a GLRT detector composed of a few high-rank subspace detectors has a slightly higher nontarget detection rate, but a significantly lower missed detection rate, than a GLRT detector composed of many low-rank subspace detectors. The high-rank GLRT configuration produced impressive results even with marginal data (single channel, single station, and very low time bandwidth product), which bodes well for the utility of building efficient aftershock classification systems and global monitoring systems at larger scales. However, future work is required to assess performance at the regional scale and to assess the performance of the system at detecting target events not used in the detector template creation.

58 GEOSCIENCES↗
DOE OSTI2016

Compiler-Directed Soft Error Detection and Recovery to Avoid DUE and SDC via Tail-DMR

This article presents Clover, a compiler-directed soft error detection and recovery scheme for lightweight soft error resilience. The compiler carefully generates soft-error-tolerant code based on idempotent processing without explicit checkpoints. During program execution, Clover relies on a small number of acoustic wave detectors deployed in the processor to identify soft errors by sensing the wave made by a particle strike. To cope with DUEs (detected unrecoverable errors) caused by the sensing latency of error detection, Clover leverages a novel selective instruction duplication technique called tail-DMR (dual modular redundancy) that provides a region-level error containment. Once a soft error is detected by either the sensors or the tail-DMR, Clover takes care of the error as in the case of exception handling. To recover from the error, Clover simply redirects program control to the beginning of the code region where the error is detected. The experimental results demonstrate that the average runtime overhead is only 26%, which is a 75% reduction compared to that of the state-of-the-art soft error resilience technique. In addition, this article evaluates an alternative technique called tail-wait, comparing it to Clover. According to the evaluation with the different processor configurations and the various error detection latencies, Clover turns out to be a superior technique, achieving 1.06 to 3.49× speedup over the tail-wait.

Computer Science↗
DOE OSTI2021

Programmable intrusion detection for distributed energy resources in cyber–physical networked microgrids

We present a programmable intrusion detection method is presented to identify the malicious attacks to distributed energy resources (DERs) in the cyber-physical networked microgrids. The proposed method injects small programmable signals into the system and uses the response to identify abnormal conditions. Because of the low or even zero inertia induced by integrations of DER power-electronic-interfaces, microgrids have very limited resilience capability; and thus, being sensitive to attacks. One microgrid's malfunction caused by attacks can easily propagate to its neighboring systems when several microgrids are connected, leading to catastrophic electricity supply failures. Through the presented method, malicious intrusions can be effectively detected, located, and defended for securing microgrids. Theoretical derivations are provided to define the programmable detection rules. The detection rule is easy and flexible to update, making it difficult for attack actors to gain the knowledge of the detection rules, in order to avoid being detected. Numerical results on a cyber-physical networked microgrids system show that the proposed method is effective and efficient in precisely locating intrusion attacks to the microgrids system.

42 ENGINEERING↗
DOE OSTI2020

Window obscuration sensors for mobile gas and chemical imaging cameras

An infrared (IR) imaging system for determining a concentration of a target species in an object is disclosed. The imaging system can include an optical system including a focal plane array (FPA) unit behind an optical window. The optical system can have components defining at least two optical channels thereof, said at least two optical channels being spatially and spectrally different from one another. Each of the at least two optical channels can be positioned to transfer IR radiation incident on the optical system towards the optical FPA. The system can include a processing unit containing a processor that can be configured to acquire multispectral optical data representing said target species from the IR radiation received at the optical FPA. One or more of the optical channels may be used in detecting objects on or near the optical window, to avoid false detections of said target species.

Mallery, Ryan↗
DOE OSTI2022

Window obscuration sensors for mobile gas and chemical imaging cameras

An infrared (IR) imaging system for determining a concentration of a target species in an object is disclosed. The imaging system can include an optical system including a focal plane array (FPA) unit behind an optical window. The optical system can have components defining at least two optical channels thereof, said at least two optical channels being spatially and spectrally different from one another. Each of the at least two optical channels can be positioned to transfer IR radiation incident on the optical system towards the optical FPA. The system can include a processing unit containing a processor that can be configured to acquire multispectral optical data representing said target species from the IR radiation received at the optical FPA. One or more of the optical channels may be used in detecting objects on or near the optical window, to avoid false detections of said target species.

Mallery, Ryan↗