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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

Power consumption monitoring using additional monitoring device

Today, emphasis is placed on reducing power consumption. Computers are large consumers; therefore it is important to know the total consumption of computing systems. Since their optimal functioning requires quite strict environmental conditions, without much variation in temperature and humidity, reducing energy consumption cannot be made without monitoring environmental parameters. Thus, the present work uses a multifunctional electric meter UPT 210 for power consumption monitoring. Two applications were developed: software which carries meter readings provided by electronic and programming facilitates remote device and a device for temperature monitoring and control. Following temperature variations that occur both in the cooling system, as well as the ambient, can reduce energy consumption. For this purpose, some air conditioning units or some computers are stopped in different time slots. These intervals were set so that the economy is high, but the work's Datacenter is not disturbed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

System and method for monitoring power consumption to detect malware

A system and method (referred to as the system) detects malware, viruses, and/or malicious activity by generating a direct current source power consumption profile by causing a monitored device to execute a fully automated recurrent software operation. The system receives by an automated detection system, the direct current source power consumption profile generated by an intelligent power sensor and generates by a detection engine, a power security profile that identifies suspicious code by profiling direct current consumed by monitored type devices. The system executes a detection engine remote from the monitored device that identifies an infected device.

97 MATHEMATICS AND COMPUTING↗

Towards a Cyber Defense Framework for SCADA Systems Based on Power Consumption Monitoring

Supervisory control and data acquisition (SCADA) is an industrial automation system that remotely monitor, and control critical infrastructures. SCADA systems are major targets for espionage and sabotage attackers. According to the 2015 Dell security annual threat report, the number of cyber-attacks against SCADA systems has doubled in the past year. Cyber-attacks (i.e., buffer overflow, rootkits and code injection) could cause serious financial losses and physical infrastructure damages. Moreover, some specific cyber-attacks against SCADA systems could become a threat to human life. Current commercial off-the-shelf security solutions are insufficient in protecting SCADA systems against sophisticated cyber-attacks. In 2014 a report by Mandiant stated that only 69% of organizations learned about their breaches from third entities, meaning that these companies lack of their own detection system. Furthermore, these breaches are not detected in real-time or fast enough to prevent further damages. The average time between compromise and detection (for those intrusions that were detected) was 205 days. To address this challenge, we propose an Intrusion Detection System (IDS) that detects SCADA-specific cyber-attacks by analyzing the power consumption of a SCADA device. Specifically, to validate the proposed approach, we chose to monitor in real-time the power usage of a a Programmable Logic Controller (PLC). To this end, we configured the hardware of the tetsbed by installing the required sensors to monitor and collect its power consumption. After that two SCADA-specific cyber-attacks were simulated and TracerDAQ Pro was used to collect the power consumption of the PLC under normal and anomalous scenarios. Results showed that is possible to distinguish between the regular power usage of the PLC and when the PLC was under specific cyber-attacks.

Hernandez Jimenez, Jarilyn M↗

Advanced ice protection systems test in the NASA Lewis icing research tunnel

Tests of eight different deicing systems based on variations of three different technologies were conducted in the NASA Lewis Research Center Icing Research Tunnel (IRT) in June and July 1990. The systems used pneumatic, eddy current repulsive, and electro-expulsive means to shed ice. The tests were conducted on a 1.83 m span, 0.53 m chord NACA 0012 airfoil operated at a 4 degree angle of attack. The models were tested at two temperatures: a glaze condition at minus 3.9 C and a rime condition at minus 17.2 C. The systems were tested through a range of icing spray times and cycling rates. Characterization of the deicers was accomplished by monitoring power consumption, ice shed particle size, and residual ice. High speed video motion analysis was performed to quantify ice particle size.

Bond, Thomas H.↗

Advanced ice protection systems test in the NASA Lewis Icing Research Tunnel

Tests of eight different deicing systems based on variations of three different technologies were conducted in the NASA Lewis Research Center Icing Research Tunnel (IRT) in June and July 1990. The systems used pneumatic, eddy current repulsive, and electroexpulsive means to shed ice. The tests were conducted on a 1.83 m span, 0.53 m chord NACA 0012 airfoil operated at a 4 degree angle of attack. The models were tested at two temperatures: a glaze condition at minus 3.9 C and a rime condition at minus 17.2 C. The systems were tested through a range of icing spray times and cycling rates. Characterization of the deicers was accomplished by monitoring power consumption, ice shed particle size, and residual ice. High speed video motion analysis was performed to quantify ice particle size.

Bond, Thomas H.↗

Robust Kriged Kalman Filtering

Although the kriged Kalman filter (KKF) has well-documented merits for prediction of spatial-temporal processes, its performance degrades in the presence of outliers due to anomalous events, or measurement equipment failures. This paper proposes a robust KKF model that explicitly accounts for presence of measurement outliers. Exploiting outlier sparsity, a novel l1-regularized estimator that jointly predicts the spatial-temporal process at unmonitored locations, while identifying measurement outliers is put forth. Numerical tests are conducted on a synthetic Internet protocol (IP) network, and real transformer load data. Test results corroborate the effectiveness of the novel estimator in joint spatial prediction and outlier identification.

97 MATHEMATICS AND COMPUTING↗

Rootkit detection system

A system and method (referred to as the system) detect infectious code. The system injects a repetitive software code that causes malware in a monitored device to render a detectable direct current power consumption profile. A guide wave generator generates a guide wave signal that establishes an observational window that is applied to data that represent a direct current source power consumption of the monitored device. An extraction device extracts a portion of the data that represent the direct current source power consumption of the monitored device. A deviation engine identifies the malware on the monitored device without processing data associated with a prior identification of the malware or identifying a source of the malware or identifying a location of the malware on the monitored device.

Dawson, Joel↗

Heartbeat: Detecting Malware by Periodic Power Signal Injection and Monitoring

Rootkits and other stealthy malware attempt to conceal their presence on a computer by making changes to the host computer’s operating environment. ORNL’s Heartbeat technology detects these changes, and thus the malware itself. Heartbeat operates by directly monitoring the DC power consumption of the computer while a set of operations, the “heartbeat,” is executed periodically. These operations exercise parts of the operating system that are common targets of malware tampering. The power consumption during these heartbeat events is monitored and then compared to a previously learned baseline, with any significant deviation detected and analyzed. This technology has been tested and validated in a laboratory environment, and ORNL is currently seeking a deployment partner to allow for further in-context development and testing of this technology.

97 MATHEMATICS AND COMPUTING↗

Repair and Utilization of the Kratos XSAM 800 X-Ray Photoelectron Spectrometer (XPS)

The objectives for this summer faculty fellowship were first to repair the Kratos XSAM 800 X-ray Photoelectron Spectrometer (XPS) and then to utilize the instrument to participate in ongoing research projects at KSC and in the researcher's own laboratory at UCF. The first 6 weeks were used in repairing the instrument. Working both alone and with the Kratos service engineer, a number of hardware problems, largely associated with the sample stage control system, were corrected. Defective parts were identified and fixed in the computer driver boards, the stage power supply, and the driver interface. The power supply was completely replaced. After four weeks of work, the instrument was functional. This occurred on a Wednesday. The following Friday the instrument had to be completely shut down because the power to the O & C Building was to be turned off. The instrument was properly secured. On Monday, the instrument was powered up and the original problems returned. After another 2 weeks of work, a software problem was identified. This problem caused the computer to use a defective port for the sample stage control. It was circumvented by rewriting the startup routine. The final 3 weeks of the fellowship were spent using the XPS to analyze samples being studied in the Langley materials project (Martha Williams) and a catalyst project (Dr. Orlando Melendez). During this time, several sample analysis requests from other groups at KSC also came in and those samples were run as well. The summer faculty fellowship also allowed many contacts to be made. After meeting with the sensors group, two projects were identified for collaboration and white papers are being prepared. One project aims to develop small, very sensitive hydrogen detectors and the other to develop a broad area, easily monitored, zero power consumption hydrogen detector. In addition to the work mentioned above, the XPS was utilized in a study underway in Dr. Hampton's laboratory at UCF.

Hampton, Michael D.↗

Deep Space Habitat Wireless Smart Plug

NASA has been interested in technology development for deep space exploration, and one avenue of developing these technologies is via the eXploration Habitat (X-Hab) Academic Innovation Challenge. In 2013, NASA's Deep Space Habitat (DSH) project was in need of sensors that could monitor the power consumption of various devices in the habitat with added capability to control the power to these devices for load shedding in emergency situations. Texas A&M University's Electronic Systems Engineering Technology Program (ESET) in conjunction with their Mobile Integrated Solutions Laboratory (MISL) accepted this challenge, and over the course of 2013, several undergraduate students in a Capstone design course developed five wireless DC Smart Plugs for NASA. The wireless DC Smart Plugs developed by Texas A&M in conjunction with NASA's Deep Space Habitat team is a first step in developing wireless instrumentation for future flight hardware. This paper will further discuss the X-Hab challenge and requirements set out by NASA, the detailed design and testing performed by Texas A&M, challenges faced by the team and lessons learned, and potential future work on this design.

Morgan, Joseph A.↗

Laboratory Resources and Techniques to Evaluate Smart Home Technology: Preprint

Smart home technologies promise to make residential buildings more comfortable, less costly to operate, more energy efficient, and more integrated with the grid, but these systems are difficult to evaluate in traditional laboratory spaces. To aid in the development and evaluation of new home energy management systems (HEMS), NREL built the Systems Performance Laboratory (SPL) within the Energy Systems Integration Facility. SPL has electrical infrastructure for three residential buildings, complete with smart meters, breaker panels and a full complement of major and minor appliances in each 'home.' Cord and plug power connections mean that appliances can easily be swapped for different models. Distributed energy resources (DER), such as residential photovoltaic (PV) inverters and home batteries, are also available for integration. Sensors monitor the power consumption of all loads and controllers can simulate occupancy to drive the appliances in realistic ways. A novel hardware-in-the-loop application was developed to ensure air conditioner cycling by combining a building simulation with a physical air conditioner and a thermostat, which allows us to simulate performance in any climate with any building construction. Another application of the hardware-in-the-loop technique uses a grid simulation to model the grid impact for different control strategies related to smart home technologies. This laboratory is a powerful, flexible tool that can be employed to evaluate the effect that home energy management and other smart home technologies will have at the appliance, whole-home, and distribution feeder levels - all of which are important perspectives for different stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

WattAMeter [SWR-25-101]

WattAMeter is a Python package for monitoring and recording power consumption over time, enabling users to collect time series data on CPU, GPU, and RAM power usage. It also estimates energy consumption and CO₂ emissions.

da Silva Pereira, Weslley [National Renewable Ener↗

Tunneling Barrier-Integrated Gold Nanofilms for Negative Strain Gauging with Near-Zero Energy Consumption

Wireless strain sensors with minimal power needs are essential for long-term monitoring in energy-limited environments. We present a soft tunneling barrier-integrated gold thin film for negative strain sensing with near-zero energy consumption. The device features a strain-induced transition from an insulating to a metallic state, increasing conductivity by 9 orders of magnitude under a controlled strain. It consists of Au-PDMS-Au nanofilm layers, where the Au structures are near the percolation threshold and the PDMS layer acts as a tunneling barrier. Under strain, thinning due to the Poisson effect lowers the barrier’s potential height, enabling electron tunneling and forming an electrical path. Further, with a standby power consumption of ~10 –5 mW over 10 6 times lower than conventional sensors (~12.5 mW), this device is ideal for real-time, long-term stationary structural monitoring in multiple locations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Effects-Based Monitoring of Geomagnetically-Induced Current Using a Convolutional Neural Network

Geomagnetically-induced current (GIC) due to space weather can flow in the power grid causing undesirable effects such as transformer overheating, misoperation of protection devices, and potential blackouts. It is therefore important to monitor GIC in the power grid to improve online situational awareness and decision-making of system operators during a geomagnetic disturbance. To avoid the costly installation of GIC monitors at transformers’ neutrals, it is desirable to find correlations between GIC and already-monitored parameters. Hence, this work proposed the use of a convolutional neural network (CNN) to compute GIC amplitudes from learned patterns in the time-series data of transformer even harmonic currents. Using an electromagnetic transient program, GIC injection simulations were performed for a modeled Dominion Energy Virginia (DEV) substation with two 504 MVA, 500/230 kV transformers. Data collected from these offline simulations were used to train the CNN to provide online GIC monitoring. Testing the CNN performance involved using real GIC measurements from published literature and from a physical GIC monitor in the DEV area. Finally, the results showed that the proposed method was able to provide GIC readings with a root mean squared error of 1.56 A/phase (equivalent to an average accuracy of 94%) for these real GIC waveforms.

42 ENGINEERING↗

HydraGNN v4.0

The new version of HydraGNN v4.0 provides additional core capabilities, such as: Inclusion of multi-body atomistic cluster expansion MACE, polarizable atom interaction neural network PAINN, and equivariant principal neighborhood aggregation (PNAEq) among the message passing layers supported -Inclusion of graph transformers to directly model long-range interactions between nodes that are distant in the graph topology Integration of graph transformers with message passing layers by combining the graph embedding generated by the two mechanisms, which allows for an improved expressivity of the HydraGNN architecture Improved re-implementation of multi-task learning (MTL) to allow its use for stabilized training across imbalanced, multi-source, multi-fidelity data Introduction of multi-task parallelism, a newly proposed type of model parallelism specifically for MTL architectures, which allows to dispatch different output decoding heads to different GPU devices Integration of multi-task parallelism with pre-existing distributed data parallelism to enable a 2D parallelization for distributed training Improved portability of the distributed training across Intel GPUs, which has been testes on ALCF exascale supercomputer Aurora Inclusion of 2-level fine-grained energy profilers portable across NVIDIA, AMD, and Intel GPUs to monitor the power and energy consumption associated with different functions executed by the HydraGNN code during data pre-load and training Restructuring of previous examples and inclusion of new sets of examples to illustrate the download, preprocess, and training of HydraGNN models on new large-scale open-source datasets for atomistic materials modeling (e.g., Alexandria, Transition1x, OMat24, OMol25)

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗

Sensor Network Demonstration for In Situ Decommissioning - 13332

Florida International University's (FIU's) Applied Research Center is currently supporting the Department of Energy's (DOE) Environmental Management Office of D and D and Facility Engineering program. FIU is supporting DOE's initiative to improve safety, reduce technical risks, and limit uncertainty within D and D operations by identifying technologies suitable to meet specific facility D and D requirements, assessing the readiness of those technologies for field deployment, and conducting feasibility studies and large scale demonstrations of promising technologies. During FY11, FIU collaborated with Savannah River National Laboratory in the development of an experimental test site for the demonstration of multiple sensor systems for potential use in the in situ decommissioning process. In situ decommissioning is a process in which the above ground portion of a facility is dismantled and removed, and the underground portion is filled with a cementious material such as grout. In such a scenario, the question remains on how to effectively monitor the structural health of the grout (cracking, flexing, and sinking), as well as track possible migration of contaminants within and out of the grouted monolith. The right types of sensors can aid personnel in better understanding the conditions within the entombed structure. Without sensors embedded in and around the monolith, it will be very difficult to estimate structural integrity and contaminant transport. Yet, to fully utilize the appropriate sensors and the provided data, their performance and reliability must be evaluated outside a laboratory setting. To this end, a large scale experimental setup and demonstration was conducted at FIU. In order to evaluate a large suite of sensor systems, FIU personnel designed and purchased a pre-cast concrete open-top cube, which served as a mock-up of an in situ DOE decommissioned facility. The inside of the cube measures 10 ft x 10 ft x 8 ft. In order to ensure that the individual sensors would be immobilized during the grout pouring activities, a set of nine sensor racks were designed. The 270 sensors provided by Idaho National Laboratory (INL), Mississippi State University (MSU), University of Houston (UH), and University of South Carolina (USC) were secured to these racks based on predetermined locations. Once sensor racks were installed inside the test cube, connected and debugged, approximately 32 cubic yards of special grout material was used to entomb the sensors. MSU provided and demonstrated four types of fiber loop ring-down (FLR) sensors for detection of water, temperature, cracks, and movement of fluids. INL provided and demonstrated time differenced 3D electrical resistivity tomography (ERT), advanced tensiometers for moisture content, and thermocouples for temperature measurements. University of Houston provided smart aggregate (SA) sensors, which detect crack severity and water presence. An additional UH sensor system demonstrated was a Fiber Bragg Grating (FBG) fiber optic system measuring strain, presence of water, and temperature. USC provided a system which measured acoustic emissions during cracking, as well as temperature and pH sensors. All systems were connected to a Sensor Remote Access System (SRAS) data networking and collection system designed, developed and provided by FIU. The purpose of SRAS was to collect and allow download of the raw sensor data from all the sensor system, as well as allow upload of the processed data and any analysis reports and graphs. All this information was made available to the research teams via the Deactivation and Decommissioning Knowledge Management and Information Tool (D and D KM-IT). As a current research effort, FIU is performing an energy analysis, and transferring several sensor systems to a Photovoltaic (PV) System to continuously monitor energy consumption parameters and overall power demands. Also, One final component of this research is focusing on developing an integrated data network to capture, log and analyze sensor system data in near real time from a single interface. FIU personnel and DOE Fellows monitored the progress and condition of the sensors for a period of six months. During this time, the sensors recorded data pertaining to strain, compression, temperature, crack detection, moisture presence, fluid mobility, shock resistance, monolith movement, and electrical resistivity. In addition, FIU regularly observed the curing process of the grout and documented the cube condition via the nine racks of sensors. The sensors held up throughout the curing process, withstood the natural elements for six months, and monitored the integrity of the grout. The large scale experiment and demonstration conducted at FIU was the first of its kind to demonstrate the feasibility of state of the art sensors for in situ decommissioning applications. These efforts successfully measured the durability, performance, and precision of the sensors in question as well as monitored and recorded the curing process of the selected grout material under natural environmental conditions. The current energy analysis work is resulting in data on the constraints placed by some of the sensor systems on a power network that requires high reliability and low losses. In addition, a sensor system demonstration has determined that it is feasible to develop an integrated data network where data can be accessed in near real-time from all systems, thereby allowing for larger-scale integrated system testing to be performed. Information collected during the execution of this research project will aid decision makers in the identification of sensors to be used in nuclear facilities selected for in situ decommissioning. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Energy savings and usability of zero-client computing in office settings

This study provides a detailed comparison of the power consumption, usability, and applicability of virtual machines (VMs) - accessed through zero-client devices - and traditional laptop computers in office settings. The study analyzed high-level plug loads across two office spaces, one using traditional laptops, the other using zero clients. In addition, the individual power consumption of four workstations was monitored and compared. Each workstation user switched between using a laptop or zero client for one week and then using the alternate system the second week. Results of the high-level and workstation analysis show that average workstation plug loads are lower for occupants using zero clients. However, this does not include power consumed by the data center managing VMs. This study calculates the affiliated data center power draw of VMs and shows that server-related loads push total zero-client computing energy higher than that of traditional laptops. Finally, a questionnaire was administered to building occupants to determine the appropriateness of zero-client computing for various user groups, with the results indicating that VMs are most appropriate for more basic software functions. The findings of this study suggest that advances in server technology can help improve both the overall efficiency and the usability of zero-client computing.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗