Optimal Placement of PV Smart Inverters With Volt-VAr Control in Electric Distribution Systems
Not provided.
Computer Science↗
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Results for “engine operability”
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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A Phenomenological Thermal Spray Wall Interaction Modeling Framework Applied to a High Temperature Ignition Assistant Device
Airborne compression ignition engines must operate with reliable ignition systems to achieve proper ignition at every cycle, particularly at high altitudes. Glow-plug-based ignition-assistant (IA) devices can provide the necessary energy to preheat the fuel and ensure ignitability of the fuel-air mixture. Ignitability of liquid sprays can be facilitated via direct impingement onto the hot IA surface, however this comes with adverse effects on the IA durability. Therefore, optimizing an IA’s design requires detailed understanding of the physics of fuel spray impingement of superheated surfaces. While spray impingement on relatively low wall temperatures has been extensively studied and appropriate numerical models have been proposed through the years, fundamental understanding of high-speed liquid spray impingement on superheated walls is still elusive. This work aims to formulate a phenomenological thermal spray-wall interaction framework for modeling the film-boiling-induced heat transfer, atomization, and dispersion of fuel spray droplets impinging onto a superheated IA device. A qualitative comparison of the new phenomenological model is performed against optical experiments from the literature of an F-24 fuel spray injected onto an IA device located 12 mm away from the injector tip. The temperature of the IA was set at 1400 K. The fuel injection pressure was 400 bar, while the ambient gas pressure and temperature were 30 bar and 800 K, respectively. The performance of the phenomenological model is evaluated in comparison with two other state-of-art models from the literature. A qualitative analysis of the different spray and fuel-air mixture characteristics is performed to outline the differences in the predictions offered by the new phenomenological model and the two state-of-art spray-wall interaction models.
droplet dispersion↗
Deep Lynx: Digital Engineering Integration Hub
The construction of megaprojects has consistently demonstrated challenges for project managers in regard to meeting cost, schedule, and performance requirements. Megaproject construction challenges are common place within megaprojects with many active projects in the United States failing to meet cost and schedule efforts by significant margins. Currently, engineering teams operate in siloed tools and disparate teams where connections across design, procurement, and construction systems are translated manually or over brittle point-to-point integrations. The manual nature of data exchange increases the risk of silent errors in the reactor design, with each silent error cascading across the design. These cascading errors lead to uncontrollable risk during construction, resulting in significant delays and cost overruns. Deep Lynx allows for an integrated platform during design and operations of mega projects.
Darrington, JohnW↗
A Hands-on Course on Intensified Membrane Processes for Sustainable Water Purification
The lack in process intensification (PI) training may be limiting processes to achieve sustainability goals. Furthermore, this project developed a hands-on course on intensified membrane processes to address knowledge gaps in PI. Bench-scale activities introduced concepts of membrane separation, operating engineering-scale modules provided a near-industrial experience, and simulation software allowed modeling and optimization of a process. Student evaluations showed that the combination of modeling, experimental, and peer-instruction work helped them understand the application of theoretical concepts.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Demonstrated Low Pressure Loss Inlet and Low Equivalence Ratio Operation of a Rotating Detonation Engine (RDE) for Power Generation
Presentation. An Aerojet Rocketdyne (AR) program was funded by the National Energy Technology Laboratory (NETL), part of the U.S. Department of Energy, to evaluate the benefits of an RDE in a turbine power plant system. Aerojet Rocketdyne subcontracted a variety of support for the program with efforts in modeling, diagnostic techniques, and test campaigns. Over the span of the program more than 700 hot fire tests were conducted at 4 facilities with 7 RDE assemblies. This presentation will cover results from the final test campaign conducted by Aerojet Rocketdyne.
03 NATURAL GAS↗
Innovative Science, Technology, and Engineering Addressing the Nation's Most Challenging Problems
The Laboratory has four strategic objectives: nuclear security; mission-focused science, technology, and engineering; mission operations; and community relations. To accomplish our mission, excellence in all areas is our objective — we call that simultaneous excellence. To achieve simultaneous excellence, we apply the Safe Conduct of Research principles, an essential part of our strategy.
99 GENERAL AND MISCELLANEOUS↗
LANL Regular Employee Population and Demographics, FY15-21
This document summarizes an effort to compile and analyze the LANL regular employee population’s demographic attributes and trends between FY15-FY21 using MicroStrategy, a web-based data analytics and visualization tool. LANL’s HR Division collected and prepared data for the Weapons Program’s annual reporting activities for the 2017 through 2023 NNSA Stockpile Stewardship and Management Plan (SSMP). Los Alamos workforce data represent the fiscal year-end snapshot of the permanent employee population who are categorized by the Common Occupational Classification System (COCS). This work enables further analyses, including trends for all workforce attributes presented in the SSMPs as well as a definition of a crosswalk between COCS categorization and the internal laboratory job classification hierarchy. Data for other sites and the federal workforce, as shown in the SSMPs, are included and corresponding figures can be visualized within the MicroStrategy tool. A portable, Excel-based version of the tool was developed and shared with the multi-site workforce working group. This summary highlights selected aspects of the LANL regular workforce. The data analyses and visualizations communicate insights within three major themes regarding permanent LANL employees: 1) demographic transformation, 2) attrition, and 3) skills. Regarding demographic transformation, and consistent with the general trend across the enterprise, early career regular employees are the fastest growing group, with growth ranging between 12-34% year-to-year over the seven-year period analyzed. The data also reflect effects of internal and external factors on attrition; the large spike in separations in FY18 aligns with the contract transition from LANS to Triad and the dip in attrition between FY20-FY21 is likely a result of the global pandemic. The population of regular employees in general management, engineer, and operator COCS categories have the fastest growth rates amongst all the occupational categories. The MicroStrategy and Excel tools provide additional details and trends.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
PDV Sensitivity [Slides]
The concept of PDV sensitive is not new. But we tend not to discuss sensitivity in a rigorous, quantified way. That should change. Indeed there is a natural definition, which is just the energy of light from the target within the analysis window that gives a SNR of 10 in the frequency domain. Systems designers, diagnostic engineers, and operators should use the language of sensitivity: (1) Absolute sensitivity: nW * ns; (2) Launch power: mW or dBm; (3) Relative surface return: dB; (4) Relative sensitivity: dB * ns. This will help us design better systems, choose the correct system for the job, maintain our systems, and tune our systems.
47 OTHER INSTRUMENTATION↗
Developing and Managing Data Acquisition Software Using Spack
The Data Acquisition systems of particle physics experiments regularly push the boundaries of high-throughput computing, demanding low-latency collection of data from thousands of devices, collating data into time-sliced events, processing these events and making trigger decisions, and writing the selected data streams to disk. To accomplish these tasks, the DAQ Engineering and Operations department at Fermilab leverages multiple software libraries and builds reusable DAQ frameworks on top. These libraries must be delivered in well-defined bundles and are thoroughly tested for compatibility and functionality before being deployed to live detectors. We have several techniques used to ensure that a consistent set of dependencies can be delivered and re-created at need. We must also support active development of DAQ software components, ideally in an environment as close as possible to that of the detectors. This development often occurs across multiple packages which have to be built in concert and features tested in a consistent and reproducible manner. I will present our scheme for accomplishing these goals using Spack environments, bundle packages, and Github Actions-based CI.
Flumerfelt, Eric [Fermilab]↗
Postdoctoral insights on mentoring excellence: a framework for best practices at Sandia National labs
The Sandia National Laboratories Strategic Plan FY24-FY27, updated for FY25, outlines Sandia’s two Big Labs-wide Goals, Accelerate Innovation and Lead in Modern Engineering. The goal of Accelerate Innovation is that “by FY27, Sandia will be a leader in scientific, engineering and operational innovation and an employer of choice for highly innovative and creative talent.” Sandia’s postdocs are leaders in innovation, well-versed in emerging techniques and cutting-edge methods, and capable of acting as a highly agile technical force across domains at the lab. As a federally funded research and development center (FFRDC), Sandia National Laboratories attracts top doctoral talent by offering a unique opportunity for postdoctoral researchers to develop at the crossroads of government, academia, and industry, working in multi-disciplinary teams and performing cutting-edge, mission-specific research that responds to immediate needs of national interest. However, this creates unique opportunities and demands of both postdoctoral appointees and the Sandia staff who act as their mentors, making mentorship key to attract talent. Since 2007 the Sandia Postdoctoral Development (SPD) Board, originally Postdoc To Professional (PD2P), a networking group at Sandia composed of a voluntary board of current postdocs and two staff liaisons, has advocated for postdoctoral development within Sandia National Labs. In this white paper, SPD board members and the Sandia Postdoctoral Development Office, organized in 2019, have come together to develop a comprehensive overview of the postdoctoral mentoring landscape at Sandia National Labs as we currently know it. By scouring various forms of data from efforts since 2018, we’ve compiled a community-derived perspective on what makes postdoctoral mentorship at Sandia unique. First, we analyze working sessions held between mentors and mentees to develop a comprehensive map of who is involved in postdoctoral mentorship at the lab and how the responsibilities are divided amongst mentors and mentees. We then combine multiple forms of data, including exit surveys, annual surveys, and community workshops, to identify the specific challenges that mentors and mentees encounter at the national lab. Finally, we use text mining and sentiment analysis to analyze mentoring award data to develop an idea of what postdocs are self-identifying as excellent mentorship within the lab. It is our goal that this white paper act as an ongoing resource to the postdoc and postdoc mentoring communities and provide a firm foundation for further conversations on the future of postdoctoral mentorship at Sandia National Labs.
99 GENERAL AND MISCELLANEOUS↗
Machine-Learning-Based Rotating Detonation Engine Diagnostics: Evaluation for Application in Experimental Facilities
Real-time monitoring of combustion behavior is a crucial step toward actively controlled rotating detonation engine (RDE) operation in laboratory and industrial environments. Various machine learning methods have been developed to advance diagnostic efficiencies from conventional postprocessing efforts to real-time methods. Here this work evaluates and compares conventional techniques alongside convolutional neural network (CNN) architectures trained in previous studies, including image classification, object detection, and time series classification, according to metrics affecting diagnostic feasibility, external applicability, and performance. Real-time, capable diagnostics are deployed and evaluated using an altered experimental setup. Image-based CNNs are applied to externally provided images to approximate dataset restrictions. Image classification using high-speed chemiluminescence images and time series classification using high-speed flame ionization and pressure measurements achieve classification speeds enabling real-time diagnostic capabilities, averaging laboratory-deployed diagnostic feedback rates of 4–5 Hz. Object detection achieves the most refined resolution of 20 μs in postprocessing. Image and time series classification require the additional correlation of sensor data, extending their time-step resolutions to 80 ms. Comparisons show that no single diagnostic approach outperforms its competitors across all metrics. This finding justifies the need for a machine learning portfolio containing a host of networks to address specific needs throughout the RDE research community.
33 ADVANCED PROPULSION SYSTEMS↗
Flowability of Crumbler Rotary Shear Size-Reduced Granular Biomass: An Experiment-Informed Modeling Study on the Angle of Repose
Biomass has potential as a carbon-neutral alternative to petroleum for chemical and energy products. However, complete replacement of fossil fuel is contingent upon efficient processes to eliminate undesirable characteristics of biomass, e.g., low bulk density, variability, and storage-induced quality problems. Mechanical size reduction via comminution is a processing operation to engineer favorable biomass flowability in handling. Crumbler rotary shear mill has been empirically demonstrated to produce more uniformly shaped particles with higher flowability than hammermilled biomass. This study combines modeling and experimentation to unveil fundamental understandings of the relation between granular particle characteristics and biomass flow behavior, which elucidate underlying mechanisms and guide selection of critical processing parameters. For this purpose, the impact of critical material attributes, including particle size (2–6 mm), particle shape (briquette, chip, clumped-sphere, cube, etc.), and surface roughness, on the angle of repose (AOR) of milled pine chips were investigated using discrete element method (DEM) simulations. Forest Concepts Crumbler rotary shear system is used to produce milled pine particles within the same size range considered in DEM simulations. AOR of different sets of these particles were measured experimentally to benchmark DEM results against experimental data. Specific energy consumption for the comminution of biomass with different particle size and moisture content are measured for technoeconomic analysis. Our results show that the smaller size (2 mm) of pine particle achieves better followability (i.e., smaller AOR) while the energy cost of comminution is significantly higher and bulk density is almost the same as the 6-mm pine particles. For the 2-mm particle size, Crumbles from veneer have better flow properties than Crumbles from chips. Contrarily, no significant difference was observed between the AOR of the two materials for the 6-mm particle size. Furthermore, from DEM simulations, mechanical interlocking between particles was found as a dominant factor in determining AOR of complex-shaped particles such as milled pine, which cannot be accurately captured by using simple particle shapes (e.g., mono-sphere) with a rolling resistance model. Conversely, clumped-sphere model alleviates this limitation without increasing computational cost significantly and can be used for accurate representation of biomass granular particles when simulating free-flow behavior.
09 BIOMASS FUELS↗
Design and Optimization of a Hybrid Design for Quantum Transduction
This study presents the mechanical design and analysis of a quantum electro-optical transducer engineered to operate at millikelvin temperatures within a dilution refrigerator. The transducer enables bidirectional microwave-optical frequency conversion through a hybrid architecture that integrates a superconducting radiofrequency (SRF) cavity with an electro-optic optical cavity. Among several design options investigated, the configuration offering the best thermal and mechanical performance was selected, yielding a robust solution with reduced sensitivity to fabrication tolerances, improved heat dissipation, as well as alignment precision. The design ensures uniform temperature distribution, enabling higher laser pump powers and, thus, increased conversion efficiency, while maintaining mechanical stresses safely below the material yield strength. Electromagnetic simulations further validate the design, demonstrating enhanced coupling between the optical and microwave modes, as well as a broader tuning range achieved with smaller tuner displacements.
quantum computing↗
Power management for hybrid electric vehicles
A system and method for power management of hybrid electric vehicles is provided. In some implementations, a plug-in series hybrid electric vehicle may include an engine, a motor/generator (MG), a traction motor, an energy storage device, and a controller. The controller is coupled to the engine and the MG to control operation of the engine and the MG such that a state-of-charge (SOC) of the energy storage device tracks a dynamic reference SOC profile during a trip and an average engine power (AEP) is maintained above a threshold. In some instances, maintaining AEP above a threshold supports emission control of the vehicle.
Le, Dat Duc↗
Determining Reactor Operating Conditions to Prevent Xenon Walkaway Accident
The xenon walk-away is a postulated uncontrolled criticality that could occur if operators are forced to evacuate the control room in certain circumstances. This poster shows how previously held assumptions are not entirely valid and that less restrictions should be placed on operators and engineers than initially assumed.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Cyber-Informed Engineering Principles: What’s in it for me?
CIE is an emerging method to integrate cybersecurity considerations into the conception, design, development, and operation of any physical system that has digital connectivity, monitoring, or control. CIE complements—but does not replace—the application of cybersecurity standards or practices currently in place within an organization. Rather, it expands cybersecurity decisions into the engineering space, not by asking engineers to become cyber experts, but by calling on engineers to apply engineering tools and make engineering decisions that improve cybersecurity outcomes. CIE examines the engineering consequences that a sophisticated cyber attacker could achieve, and drives engineering changes that may provide deterministic mitigations to limit or eliminate those consequences. Engineers and technicians that design critical energy infrastructure installations can integrate the 12 principles of CIE into each phase of the engineering lifecycle, from concept to retirement. These principles are aimed at system or design engineers, operators, and technicians, rather than software engineers or operational cybersecurity practitioners, because the engineers who design, build, operate, and maintain the physical infrastructure are best positioned to leverage a system’s engineering design to diminish the severity of cyber attacks or digital technology failures. This approach creates new opportunities for engineering teams—and not just cybersecurity teams—to secure the system using the physics and mechanics of engineering controls—not just digital monitoring and controls.
99 GENERAL AND MISCELLANEOUS↗
In-Use Passenger Vessel Emission Rates of Black Carbon and Nitrogen Oxides
This study quantified emission factors of black carbon (BC) and nitrogen oxides (NO x ) from 21 engines on in-use excursion vessels and ferries operating in California's San Francisco Bay, including EPA uncertified and Tier 1-4 engines and across engine operating modes. On average, ~60 fuel-based emission factors per engine were measured using a novel combination of exhaust plume capture combined with GPS location and speed data that can be more readily deployed than common portable emissions measurement systems. Here, BC and NO x emission factors (g kg -1 ) were lowest and least variable during fast cruising and highest during maneuvering and docked operation. Selective catalytic reduction (SCR) reduced NO x emissions by ~80% when functional. However, elevated NO x emissions that exceeded corresponding exhaust standards were measured on most Tier 3 and Tier 4 engines sampled, which can be attributed to inactive SCR during frequent low engine load operation. In contrast, BC emissions exceeded the PM emission standard for only one engine, and SCR systems employed as a NO x reduction technology also reduced emitted BC. Using these measured emission factors to compare commuting options, we show that the CO 2 -equivalent emissions per passenger-kilometer are comparable when commuting by car and ferry, but BC and NO x emissions can be several to more than ten times larger when commuting by ferry.
54 ENVIRONMENTAL SCIENCES↗
Reducing Methane Emissions with an Engine Fuel Reformer
Southwest Research Institute (SwRI) designed and demonstrated a compact, plasma-based fuel reformer designed to reduce methane leaks from natural-gas engines used in pipeline compression and industrial power applications. The system uses pulsed electrical discharges to convert a small portion of methane (CH4) into hydrogen (H2) and light hydrocarbons, promoting more complete combustion and reducing unburned methane in the exhaust. The reformer was evaluated through bench-scale testing, high-flow facility testing, and engine-integration testing on representative low-speed and high-speed natural-gas engines. Measured methane-leak reductions ranged from 1 to 27 percent, depending on engine type and operating condition, while reformer energy consumption remained below one percent of total engine output. Design refinements addressed thermal and electrical challenges, resulting in reliable operation with minimal impact on engine control systems. The project achieved all performance objectives within budget and schedule, produced a patentable pulsed-power system design, and established a scalable, energy-efficient pathway for mitigating methane leaks from existing natural-gas engine infrastructure.
03 NATURAL GAS↗