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At least 613 records · Page 34

A distributed scheduling algorithm for heterogeneous real-time systems

Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.

Zeineldine, Osman↗

Quantitative Evaluation of Reliability Improvement: Case Study on a Self-healing Distribution System

In this work, we develop a methodology and tool to quantitatively evaluate the reliability of a self-healing system that considers practical distribution system features such as the distributed energy resources, microgrids, and service restoration strategies. Also, this paper addresses various practical issues when being applied to an actual Duke Energy distribution system, including the design of feasible and practical service restoration strategies that are used to identify the customer interruptions after a fault, and the incorporation of the utility’s historical reliability indices that are used to calibrate the failure rate and repair time of distribution system components such as overhead lines and underground cables. This case study demonstrates the effectiveness of the proposed method.

Dong, Jiaojiao↗

Quantitative Evaluation of Reliability Improvement: Case Study on a Self-healing Distribution System

In this work, we develop a methodology and tool to quantitatively evaluate the reliability of a self-healing system that considers practical distribution system features such as the distributed energy resources, microgrids, and service restoration strategies. Also, this paper addresses various practical issues when being applied to an actual Duke Energy distribution system, including the design of feasible and practical service restoration strategies that are used to identify the customer interruptions after a fault, and the incorporation of the utility's historical reliability indices that are used to calibrate the failure rate and repair time of distribution system components such as overhead lines and underground cables. This case study demonstrates the effectiveness of the proposed method.

Dong, Jiaojiao↗

Spacecraft telemetry and command

Probability distribution of time to first loss of lock investigated by second order phase-locked loop - spacecraft telemetry and command

PHASE LOCK↗

Development of confidence limits by pivotal functions for estimating software reliability

The utility of pivotal functions is established for assessing software reliability. Based on the Moranda geometric de-eutrophication model of reliability growth, confidence limits for attained reliability and prediction limits for the time to the next failure are derived using a pivotal function approach. Asymptotic approximations to the confidence and prediction limits are considered and are shown to be inadequate in cases where only a few bugs are found in the software. Departures from the assumed exponentially distributed interfailure times in the model are also investigated. The effect of these departures is discussed relative to restricting the use of the Moranda model.

Dotson, Kelly J.↗

A Lumped Stochastic Model of Coupled Neutronic Assemblies

The objective of the present work is to apply the Harris ansatz to coupled assemblies in a lumped setting, i.e., ignoring the neutron phase dependence, which hitherto has not been considered. A Master equation for the single-time joint distribution of neutron number in each assembly, accounting for transfer of neutrons from one assembly to another via leakage transition probabilities and intercept or view factors is derived from which equations for the mean and variance in each assembly are developed. Because of the neutronic coupling, it is necessary to additionally compute the correlation function between pairs of assemblies which gives an expanded set of moment equations to solve. The reactivity of each assembly is allowed to vary with time, although a formal mechanism that is responsible for reactivity coupling between assemblies is not considered or proposed. Following Harris, it is then hypothesized that the number distribution in each assembly is a gamma distribution with assembly-specific mean and variance computed exactly from the moment equations. Illustrative numerical results are presented for the moments of a system of four coupled assemblies under various reactivity and neutronic coupling scenarios. The gamma distribution is then used to compute the probability that the neutron population exceeds a threshold value in any assembly. The report concludes with a discussion of recommended further work on this problem.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Development of a Distribution Optimal Power Flow Federate for Open-Source OEDI-SI Platform

Increasing numbers of distributed generators in the electric power distribution networks require developing a control strategy to optimize solutions in real time. Linearized optimal distribution flow development has seen growth and acceptance in the distribution systems literature for efficiently modeling the \glspl{opf} for distribution systems. This paper examines the implementation and integration procedure for linearized optimal distribution flow federate to \gls{oedisi} platform. Specifically, we discuss i) the usage of the \gls{oedisi} platform, ii) obtaining a tractable solution using developed \gls{opf} federate, and iii) validation of solutions and bench-marking the \gls{oedisi} platform with developed \gls{opf} federate using OpenDSS. In brief, we demonstrate how a general linearized optimal distribution flow federate can be developed and integrated with a co-simulation environment to mimic real-world examples. The efficacy of the proposed method is demonstrated using the IEEE 123-bus test system under different scenarios to obtain a tractable solution and compare its results.

Sadnan, Rabayet↗

Convective Melting of Particles in Flow Under Microgravity Conditions

Study of melting of dispersed or packed solid particles in a fluid under gravity and microgravity conditions provides benchmark information for many engineering applications such as material processing, environmental assessment and protection and space fire protection. During such processes, packed or dispersed solid particles are interacting with fluid flow at above-melting temperatures. By unmasking the buoyancy effects in coupled flow, phase change and heat transport phenomena, a better understanding of melting rate in non-thermal equilibrium, convective conditions can be studied. A series of flight experiments were conducted onboard the NASA KC-135 Microgravity Research Airplane. The Particle Melting in Plow (PMF) module was designed to allow flow through the initially packed ice particles at controlled temperature and velocity. To achieve this, a close-loop flow system was designed. Video images were taken to record the visualization of the melting process, from which a time variation of packed particle thickness distribution at different times can be obtained by the image analysis method. The fluid temperature distribution within the melting zone is measured by thermocouples. An infrared camera was mounted from the top of the test section to record the ice-water thermal images at a given location. The results from thermal images yield local temperature variation between melting solid and liquid and local Stephan number. Typical results for a number of cases are presented. The mathematical model, describing mass, energy, and momentum balance equations for the liquid and solid phases, is presented. It is found that melting rate is influenced mainly by the ratio of Reynolds number (based on the initial particle diameter) to the Froud number, and Stephan number. At the absence of gravity, Froud number approaches zero, Reynolds number and Stephan number become dominant factors governing the melting rate. The numerically determined results are compared with the experimental ones. It is found that the discrepancy between the predicted and measured melting rate is largely due to the inaccuracy in the constitutive equations for effective thermal physical properties, such as effective thermal conductivity and diffusivity, and transport properties, such as particle interaction coefficient, and local heat transfer coefficient of particles.

Stewart, C.↗

Combustion Instabilities Modeled

NASA Lewis Research Center's Advanced Controls and Dynamics Technology Branch is investigating active control strategies to mitigate or eliminate the combustion instabilities prevalent in lean-burning, low-emission combustors. These instabilities result from coupling between the heat-release mechanisms of the burning process and the acoustic flow field of the combustor. Control design and implementation require a simulation capability that is both fast and accurate. It must capture the essential physics of the system, yet be as simple as possible. A quasi-one-dimensional, computational fluid dynamics (CFD) based simulation has been developed which may meet these requirements. The Euler equations of mass, momentum, and energy have been used, along with a single reactive species transport equation to simulate coupled thermoacoustic oscillations. A very simple numerical integration scheme was chosen to reduce computing time. Robust boundary condition procedures were incorporated to simulate various flow conditions (e.g., valves, open ends, and choked inflow) as well as to accommodate flow reversals that may arise during large flow-field oscillations. The accompanying figure shows a sample simulation result. A combustor with an open inlet, a choked outlet, and a large constriction approximately two thirds of the way down the length is shown. The middle plot shows normalized, time-averaged distributions of the relevant flow quantities, and the bottom plot illustrates the acoustic mode shape of the resulting thermoacoustic oscillation. For this simulation, the limit cycle peak-to-peak pressure fluctuations were 13 percent of the mean. The simulation used 100 numerical cells. The total normalized simulation time was 50 units (approximately 15 oscillations), which took 26 sec on a Sun Ultra2.

Paxson, Daniel E.↗

Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from Radar: SUMO Default vs. Radar-Measured CF model Parameters

In this study, the physical principles governing car-following (CF) behavior and their impact on traffic flow at signalized intersections are investigated. High temporal-resolution radar data is used to provide valuable insights into actual CF behavior, including acceleration, deceleration, and time headway distribution. Demand-calibrated SUMO simulations are run using empirical CF parameter distributions, and three CF models are evaluated: IDM, EIDM, and Krauss. By emulating radar data in SUMO and processing simulated vehicle traces, discrepancies between empirical and simulated parameter distributions are identified. Further analysis includes comparisons with default SUMO CF model parameters. The findings reveal that measured accelerations differ from CF model parameter accelerations and using the empirical value ($\mu = 0.89m/s^2$) leads to unrealistic simulations that fail volume-based calibration. Default parameters for all three models reasonably approximate the mean and median of measured parameters, but fail to capture the true distribution shape, partly due to homogeneity when using default parameters. The results show that it is more effective to simulate with the default parameters provided by SUMO rather than using measurements of real-world distributions without additional calibration. Future work will investigate closing the loop between the measured real-world and SUMO distributions using traditional calibration tactics, as well as assess the impact of calibrated vs. default CF parameters on simulation outputs like fuel consumption.

Schrader, Max (ORCID:0000000336737672)↗

Rapid mapping of electrochemical processes in energy-conversion devices

Electrochemical impedance spectroscopy (EIS) is ubiquitously applied to identify physicochemical processes governing the performance of energy-conversion devices. However, deconvolution and interpretation of impedance phenomena are limited by measurement throughput and a dearth of scalable analysis methods. Here, we demonstrate an approach to quickly collect and coherently analyze large volumes of electrochemical data. In this study, we accelerate impedance characterization by combining rapid measurements in time and frequency domains, which are interpretably transformed using the distribution of relaxation times (DRT) and a new distribution of phasances (DOP) model. This method provides excellent agreement with EIS and decreases measurement time by an order of magnitude. High-throughput spectra are then distilled into detailed electrochemical maps. This approach is applied to a Li-ion battery and a protonic ceramic electrochemical cell as practical case studies, demonstrating how mapping can richly characterize physicochemical relationships that are difficult to decipher with conventional measurement and analysis methods.

25 ENERGY STORAGE↗

A High-resolution Model of Field-aligned Currents Through Empirical Orthogonal Functions Analysis (MFACE)

Ten years of CHAMP magnetic field measurements are integrated into MFACE, a model of field-aligned currents (FACs) using empirical orthogonal functions (EOFs). EOF1 gives the basic Region-1/Region-2 pattern varying mainly with the interplanetary magnetic field Bz component. EOF2 captures separately the cusp current signature and By-related variability. Compared to existing models, MFACE yields significantly better spatial resolution, reproduces typically observed FAC thickness and intensity, improves on the magnetic local time (MLT) distribution, and gives the seasonal dependence of FAC latitudes and the NBZ current signature. MFACE further reveals systematic dependences on By, including 1) Region-1/Region-2 topology modifications around noon; 2) imbalance between upward and downward maximum current density; 3) MLT location of the Harang discontinuity. Furthermore, our procedure allows quantifying response times of FACs to solar wind driving at the bow shock nose: we obtain 20 minutes and 35-40 minutes lags for the FAC density and latitude, respectively.

CHAMP↗

Building efficiency, electrification, and distributed solar PV bill savings under time-based retail rate designs

Building energy technologies and distributed generation, including energy efficiency (EE), distributed solar PV (DPV), and building electrification, are critical to meeting decarbonization goals. Rate design may play an important role in determining the customer economics of adopting these technologies, but it is unclear whether – and to what extent – current rate design trends support or impede progress toward these goals. In this study, we answer these questions by quantifying the range of residential customer bill impacts of EE, DPV, and building electrification investments under current and emerging time-based retail electricity rate designs (i.e., time-of-use, event-based pricing, coincident demand charges, and real time pricing). We also compare these customer bill savings to power system and societal benefits and assess how well the investments are compensated relative to the societal value they provide.

14 SOLAR ENERGY↗

Preliminary results from the White Sands Missile Range sonic boom propagation experiment

Sonic boom bow shock amplitude and rise time statistics from a recent sonic boom propagation experiment are presented. Distributions of bow shock overpressure and rise time measured under different atmospheric turbulence conditions for the same test aircraft are quite different. The peak overpressure distributions are skewed positively, indicating a tendency for positive deviations from the mean to be larger than negative deviations. Standard deviations of overpressure distributions measured under moderate turbulence were 40 percent larger than those measured under low turbulence. As turbulence increased, the difference between the median and the mean increased, indicating increased positive overpressure deviations. The effect of turbulence was more readily seen in the rise time distributions. Under moderate turbulence conditions, the rise time distribution means were larger by a factor of 4 and the standard deviations were larger by a factor of 3 from the low turbulence values. These distribution changes resulted in a transition from a peaked appearance of the rise time distribution for the morning to a flattened appearance for the afternoon rise time distributions. The sonic boom propagation experiment consisted of flying three types of aircraft supersonically over a ground-based microphone array with concurrent measurements of turbulence and other meteorological data. The test aircraft were a T-38, an F-15, and an F-111, and they were flown at speeds of Mach 1.2 to 1.3, 30,000 feet above a 16 element, linear microphone array with an inter-element spacing of 200 ft. In two weeks of testing, 57 supersonic passes of the test aircraft were flown from early morning to late afternoon.

Willshire, William L., Jr.↗

Fully Distributed Acoustic and Magnetic Field Monitoring Via a Single Fiber Line for Optimized Production of Unconventional Resource Plays

This is the final technical report for the Virginia Tech Center for Photonics Technology (VT-CPT) research project entitled “Fully Distributed Acoustic and Magnetic Field Monitoring Via a Single Fiber Line for Optimized Production of Unconventional Resource Plays”. In the the four-year effort, VT-CPT collaborated with the Departments of Mathmatics at VT and Sentek Instrument, LLC (Sentek) to develop a fiber-optic sensing system capable of real-time simultaneous distributed measurement of multiple subsurface, drilling, and production parameters. The ultra-sensitive fiber optic distributed acoustic sensing technology, picoDAS, developed by Sentek was integrated with a novel multi-material optical sensing fiber fabricated by CPT-VT to obtain distributed acoustic and magnetic field measurements with ultrahigh sensitivity and high spatial resolution. The sensing technology successfully developed and demonstrated under this research program is truly unique has application beyond subsurface imaging to include carbon storage and electrical grid monitoring, as well as healthcare and nuclear fusion. The project, sponsored by the Advanced Technology Program, began in 2019 and had the original goal of developing the next generation of harsh environment sensing systems. Exhaustive theoretical modeling was performed to optimize the multi-material optical fiber design. VT developed the processing techniques employed to successfully fabricate single mode fibers with metal cladding wires. Sensing fibers with nickel and Metglas cladding wires were fully characterized, inscribed with sensors, and fully integrated with the picoDAS system. Laboratory scale testing was performed to demonstrate performance upon exposure to lateral and transverse magnetic fields. Preliminary field trials were performed for prototype magnetic and acoustic sensing systems upon near surface deployment at VT. The distributed acoustic and magnetic field sensing system was advanced from a (Technology Readiness Level) TRL=2 to a TRL=5 via laboratory scale system validation in relevant environments. The truly one-of-its kind distributed magnetic and acoustic sensing system is expected to find immediate applications that require subsurface monitoring, to include carbon storage site monitoring, and has the potential to be a distributive technology in healthcare and electric grid markets. The technologies developed by Virginia Tech’s Center for Photonics Technology will support the mission of the National Energy Technology Laboratory (NETL) to drive innovation and deliver solutions for an environmentally sustainable and prosperous energy future by ensuring affordable, abundant, and reliable energy that drives a robust economy and national security. Technical accomplishments during the program are summarized briefly here and described in detail in the remainder of the report.

02 PETROLEUM↗

Macroecological distributions of gene variants highlight the functional organization of soil microbial systems

Abstract The recent application of macroecological tools and concepts has made it possible to identify consistent patterns in the distribution of microbial biodiversity, which greatly improved our understanding of the microbial world at large scales. However, the distribution of microbial functions remains largely uncharted from the macroecological point of view. Here, we used macroecological models to examine how the genes encoding the functional capabilities of microorganisms are distributed within and across soil systems. Models built using functional gene array data from 818 soil microbial communities showed that the occupancy-frequency distributions of genes were bimodal in every studied site, and that their rank-abundance distributions were best described by a lognormal model. In addition, the relationships between gene occupancy and abundance were positive in all sites. This allowed us to identify genes with high abundance and ubiquitous distribution (core) and genes with low abundance and limited spatial distribution (satellites), and to show that they encode different sets of microbial traits. Common genes encode microbial traits related to the main biogeochemical cycles (C, N, P and S) while rare genes encode traits related to adaptation to environmental stresses, such as nutrient limitation, resistance to heavy metals and degradation of xenobiotics. Overall, this study characterized for the first time the distribution of microbial functional genes within soil systems, and highlight the interest of macroecological models for understanding the functional organization of microbial systems across spatial scales.

59 BASIC BIOLOGICAL SCIENCES↗

Heat-death by volcano - how Venus went rogue?

The idea of a habitable Venus epoch has gained traction in recent years via 1-D and 3-D General Circulation Modeling (GCM) efforts [1,2,3]. Although recent work has supported an alternative permanent hot and dry scenario [4]. However, the habitable scenario presents us with a conundrum - how does a terrestrial planet transform from temperate to hot-house? For decades it was proposed that the gradual brightening of the sun was the probable cause [5]. Yet 4 billion years ago Venus was receiving nearly 1.4 times the insolation that Earth receives today, and many studies have put Earth at the inner boundary of the habitable zone today [6]. The newer 3-D GCM efforts have demonstrated that if Venus had an early habitable period, that the cloud-albedo feedback responsible for maintaining temperate surface conditions [7] could still be in operation today. From this perspective increasing insolation through time cannot be an answer to the transition from habitable to hot-house. We propose that the 'Great Climate Transition' (GCT) was trigged by simultaneous large igneous provinces (LIPs) akin to those like the Siberian Traps responsible for the End Permian [8]. We have taken the most up to date LIP database for Earth [9] and characterized their distribution through time as random or nearly random. Next we initiate a large suite of Monte Carlo simulations based on this record and generate the likelihood for simultaneous, or environmentally overlapping events in this hypothetical setup. We find the probability of such events to be quite high, a probable cause for Venus' GCT, and a possible harbinger of things to come for Earth.

Venus↗

Model for radial dependence of frequency distributions for energy imparted in nanometer volumes from HZE particles

This paper develops a deterministic model of frequency distributions for energy imparted (total energy deposition) in small volumes similar to DNA molecules from high-energy ions of interest for space radiation protection and cancer therapy. Frequency distributions for energy imparted are useful for considering radiation quality and for modeling biological damage produced by ionizing radiation. For high-energy ions, secondary electron (delta-ray) tracks originating from a primary ion track make dominant contributions to energy deposition events in small volumes. Our method uses the distribution of electrons produced about an ion's path and incorporates results from Monte Carlo simulation of electron tracks to predict frequency distributions for ions, including their dependence on radial distance. The contribution from primary ion events is treated using an impact parameter formalism of spatially restricted linear energy transfer (LET) and energy-transfer straggling. We validate our model by comparing it directly to results from Monte Carlo simulations for proton and alpha-particle tracks. We show for the first time frequency distributions of energy imparted in DNA structures by several high-energy ions such as cosmic-ray iron ions. Our comparison with results from Monte Carlo simulations at low energies indicates the accuracy of the method.

Non-NASA Center↗