Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “small projects”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Standoff Detection of Chemical Plumes Using Swept-ECQCL Remote Detection Technology: Results from EMRTC Complex Terrain Dual Tracer Experiment

As part of the Complex Terrain Dual Tracer Experiments performed in support of the LYNM program, a swept-wavelength external cavity quantum cascade laser (swept-ECQCL) remote detection system was deployed to measure chemical plume propagation with high temporal resolution. The swept-ECQCL remote detection technology was initially developed at PNNL, and is now under further development at Opticslah, LLC under SBIR funding from DOE (DOE SBIR Phase I Project DE-SC0019855, Remote Detection Technologies, Program Manager Chris Ramos). The swept-ECQCL technology provides a single-frequency infrared laser source which is rapidly scanned over a large wavelength range to measure the infrared absorption of gases, liquids, or solids. Analysis of the measured infrared absorption spectrum is used to detect, identify, and quantify the chemical species which are present. While most previous laser-based techniques used small wavelength tuning ranges to measure only a few isolated spectral lines of a few species, the swept-ECQCL provides the large tuning range needed to measure multiple species simultaneously, and to detect broad absorption features from large molecules or condensed phase materials. In addition, the swept-ECQCL systems have high enough spectral resolution and sensitivity to measure narrow lines of small molecules and determine isotope ratios. The remote detection system for gas plumes is based on the swept-ECQCL technology, and consists of a swept-ECQCL source, infrared detector, control electronics, and beam transmitting and alignment optics. The remote detection system directs the infrared output of the swept-ECQCL to a target retro reflector typically located at ~10-10,000 m distance. The swept-ECQCL wavelength is varied continuously over a large wavelength range (>1000 nm) at rates up to 1000 Hz. The swept ECQCL light reflected from the remote target is collected and focused onto an infrared photodetector. By measuring the detector signal continuously as the swept-ECQCL wavelength is varied, a time-series of absorption spectra are measured for the gases along the beam line of-sight. Based on analysis and fitting of the measured absorption spectra, the time-dependent chemical concentrations of species are determined. Multiple species and mixtures can be detected simultaneously, for all species with absorption features above the sensor noise floor. The sensor output is thus a continuous, high-speed record of identified chemicals along with their concentrations and isotope ratios of interest. The high-speed operation enables low-noise operation in conditions of atmospheric turbulence and allows tracking of fluctuating concentrations in transient chemical plumes as needed for reliable remote detection applications. All components operate with minimal cooling requirements and no cryogens are needed. In addition, the output infrared light is invisible with an intensity below the maximum permissible exposure (MPE) threshold of 100 mW/cm2 for these infrared wavelengths and thus eye safe. The measurement concept for plume detection using the swept-ECQCL remote detection system is as follows. The ECQCL beam is directed toward a remote retro-reflector, which reflects the beam back to the ECQCL system where it is focused onto an infrared photodetector. The line-of-sight from the ECQCL system to the retro-reflector defines the measurement path. The detected infrared signal is recorded continuously and detects the absorption of molecular species along the measurement path. Before a plume release, the system measures absorption from atmospheric constituents, which in this LWIR band consist primarily of lines from H 2 O and CO 2 , with additional weaker absorption from N 2 O, NH 3 , and O 3 possibly contributing. The system then measures any changes in absorption due to the tracer compounds when they enter the measurement path. The shape of absorption features is used to distinguish and identify the different tracer compounds, and the strength of the absorption is used to determine the path-integrated concentration – also called the column density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

3D modeling of the Staged Z-pinch with the FLASH code

The Staged Z-pinch (SZP) fusion concept is a magneto-inertial compression scheme developed by Magneto-Inertial Fusion Technologies, Inc. (MIFTI), in which small amounts of fusion fuel are brought to fusion-relevant conditions by passing multi-million amperes strong current through a cylindrical shell of high atomic number material. One- and two-dimensional modeling performed by MIFTI with the MACH2 code, suggests that net fusion energy gain can be achieved when currents in the 10 million amperes range compress a 50%-50% mixture of deuterium and tritium gas. In this project we enhance and use the FLASH code to execute high-fidelity, simulations of various SZP configurations, a collaboration between the Flash Center for Computational Science at the University of Rochester and the Laboratory for Laser Energetics, and MIFTI. FLASH is a high-performance computing, multi-physics, radiation magnetohydrodynamic (MHD) code with extended physics capabilities, which is developed at the Flash Center. The goal of this project is to assess the shell/fuel stability of the pinch to two- and three-dimensional MHD instabilities and to utilize FLASH’s extended physics capabilities to understand how extended-MHD effects impact implosion dynamics and plasma conditions at stagnation. The project is a natural extension of an ongoing collaborative effort between MIFTI and the Flash Center through the U.S. DOE Advanced Research Projects Agency-Energy (ARPA-E) BETHE program and can provide MIFTI with simulation capabilities that are currently beyond their reach with MACH2. Ultimately, MIFTI wants FLASH to become one of their simulation workhorses for reliable, high-fidelity SZP platform design. During the project, the Flash Center team developed a suite of in one- and two-dimensional FLASH simulations to model different variants of the SZP platform, performed code-to-code comparisons with MACH2, and used the FLASH code to design and model SZP experiments like the Double Eagle experiments that MIFTI recently performed. Also, the Flash Center team developed the capabilities of FLASH to be able to do three-dimensional simulations of pulsed-power experiments with the code for the first time. Two publications from this effort are currently under review and two more are in preparation. MIFTI has also committed to the use of FLASH for future SZP simulation efforts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Science Driven Discovery of Nanoparticle Photocatalysts

Photocatalytic water splitting using suspensions of nanoparticle photocatalysts is a promising route to economically sustainable production of green hydrogen. The principal challenge is to develop photocatalysts with overall solar-to-hydrogen conversion efficiency that exceeds 10 percent. In this project we have developed a new platform for investigating candidate materials for photocatalytic water splitting. Our platform consists of patterned Au electrodes and a Ag/AgCl reference electrode on an insulating substrate onto which we disperse nanoparticle photocatalysts. We then cover the substrate with a thin layer of ionogel containing a protic ionic liquid that dissolves water from the ambient. Using this platform we have demonstrated photoelectrochemical activity mapping for single and small clusters of BiVO 4 nanoparticle photocatalysts and correlated these results to their Raman and photoluminescence spectra. The preliminary results suggest a strong correlation for low efficiency nanoparticles, followed by saturation for those with higher activities, indicating that interface reaction or electrolyte transport become the limiting factor. We anticipate that further application of this platform to investigation of candidate photocatalyst materials will provide useful insights into the mechanisms that limit their performance.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Planar Systems for Quantum Information

This project aims to develop two‐dimensional (2D) moiré materials as a quantum simulator to implement model Hamiltonians and their phase diagrams. Progress in quantum information science (QIS) requires the development of advanced quantum materials systems. The rich family of layered van der Waals materials and their heterostructures present opportunities to create previously unrealized types of applications for QIS. Specifically, when two layers of van der Waals materials are overlaid with a small twist angle or/and lattice mismatch, a moiré superlattice with a period of about ten nanometers is formed. This provides a periodic trapping potential for electrons. Electrons can tunnel between the traps and repel each other by their mutual Coulomb interactions. The platform of 2D moiré materials provides many attractive features, including tunability of length and energy scales, charge density, and even lattice symmetry. It presents new possibilities for realizing quantum simulation of the many-body physics in a solid-state platform. This integrated team of six investigators seeks to develop relevant theoretical treatments to link ab-initio studies of 2D moiré materials to model Hamiltonians and to evaluate correlated phases predicted by these model Hamiltonians in the relevant regimes. On the experimental side, the team aims to develop methods to realize a homogeneous and highly controlled potential landscape for the electrons and to initiate, protect, and measure their quantum many-body states.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Split HPWHs as an Efficient Solution for Multifamily Buildings with In-Unit Water Heaters

A quarter of all housing units in the United States are found in multifamily buildings, but few efficiency innovations have been made to improve electric water heating systems in this building type. Domestic hot water in multifamily buildings can either be provided by a large central water heater or smaller in-unit water heaters. Integrated heat pump water heaters that are installed in single-family homes are often a poor fit for individual multifamily units because the water heaters are often located in small internal closets. This confined space can limit the airflow to the heat pump, and the cold exhaust air can cause discomfort and reduced efficiency. Split CO2 HPWHs separate the tank from the heat pump, which allows for installation location flexibility. Further, CO2 heat pumps can operate under colder ambient conditions, making them a better fit for multifamily units across a wide range of climate regions. As part of a larger project to characterize split HPWH performance, we evaluated the feasibility of installing an additional, parallel tank that could provide hot water to a second housing unit using a single CO2 heat pump. This approach would reduce the first costs of these more expensive units. Based on the high draw volume that we imposed on both tanks, the same heat pump may be able to support more tanks, depending on hot water usage. This paper will describe the split CO2 HPWH technology, how the two-tank system was controlled, and results from our laboratory evaluation.

CO2 HPWH↗
DOE OSTI2022

A deep-learning based raw waveform region-of-interest finder for the liquid argon time projection chamber

The liquid argon time projection chamber (LArTPC) detector technology has an excellent capability to measure properties of low-energy neutrinos produced by the sun and supernovae and to look for exotic physics at very low energies. In order to achieve those physics goals, it is crucial to identify and reconstruct signals in the waveforms recorded on each TPC wire. In this work, we report on a novel algorithm based on a one-dimensional convolutional neural network (CNN) to look for the region-of-interest (ROI) in raw waveforms. We test this algorithm using data from the ArgoNeuT experiment in conjunction with an improved noise mitigation procedure and a more realistic data-driven noise model for simulated events. This deep-learning ROI finder shows promising performance in extracting small signals and gives an efficiency approximately twice that of the traditional algorithm in the low energy region of ~0.03–0.1 MeV. This method offers great potential to explore low-energy physics using LArTPCs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Simulation of Microcapsule Transport in Fractured Media Using Coupled CFD‐DEM

Geothermal energy is sustainable and gaining momentum as a solution to energy crises and environmental issues. However, challenges like production temperature and thermal breakthrough can impact geothermal project efficiency. One innovative solution to alleviate the thermal breakthrough is to inject polymer-based materials that are encapsulated in microcapsules into fractures to modify fracture permeability and prevent preferential flow. In our study, we utilized a coupled computational fluid dynamics and discrete element method to simulate the transport of microcapsules under various scenarios controlled by microcapsule size, microcapsule concentration, and fracture roughness. For a smooth fracture, the results indicate that small microcapsules can travel through a smooth fracture regardless of their concentrations. Large microcapsules can transport through a smooth fracture when present in lower concentrations. However, medium and mixed-size microcapsules tend to cause the sealing of a smooth fracture, irrespective of their concentrations. For a rough fracture, the transport of microcapsules is complicated by their interactions with the rough fracture walls. The presence of two sealing positions in a rough fracture adds further complexity to this transport phenomenon. The size and concentration of microcapsules control one sealing location, while the rough fracture walls determine the other sealing location. The rough walls substantially affect microcapsule transport, rendering the role of microcapsule size and concentration less significant. The simulation results suggest that complex fracture surfaces significantly elevate the occurrence of sealing behavior. To mitigate sealing behavior within more complex fractures, it would be beneficial to use smaller and lower concentrations of microcapsules.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Wavefront Preservation in Soft X-Ray Beamlines for the Advanced Light Source Upgrade

In the 4th generation of X-ray light sources, including Free-Electron Lasers (FEL) and Diffraction-Limited Storage Rings (DLSR), the emittance of the electron beam is small or negligible compared to the emittance of the photon beam produced by insertion devices, thus generating coherent beams of light. Over the next few years, several lightsource facilities will be built or upgraded to produce X-ray beams of unprecedented coherent flux. Delivering these exceptional beams to the sample chambers requires beamline optical systems that are designed to preserve the wavefront properties. Our goal in the Advanced Light Source upgrade project (ALS-U) is to create a new class of beamlines that reach diffraction-limited X-ray optical quality through tightly integrated, efficient optical systems, diagnostics, and adaptive mirrors, thus providing users with new scientific capabilities offered by coherent X-ray light interactions with matter. Herein we describe aspects of the beamlines’ design as they enter the project’s final design phase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Supporting ARPA-E Power Grid Optimization (Final Report)

Pacific Northwest National Laboratory (PNNL), Arizona State University (ASU), Georgia Institute of Technology (Georgia Tech), Los Alamos National Laboratory (LANL), National Renewable Energy Laboratory (NREL), Texas A&M University (TAMU), The University of Texas at Austin (UT), and the University of Wisconsin-Madison (UW-M) supported the ARPA-E Grid Optimization (GO) Competition by providing a common problem formulation, data format, datasets, evaluation mechanism, scoring, rules, and results that resulted in the awarding of $\$9.24$ million dollars to teams from academia, industry, and national labs for solving three sets of increasingly difficult non-linear, security- constrained AC Optimal Powerflow (AC-OPF) optimization problems in order to increase the efficiency of the US Electric Grid. It is estimated that a 1% increase in efficiency can save $\$1$ billion. Current industry practices typically use a linear DC model (DC-OPF) in order solve the OPF problem within the time constraints of the operation schedule. The GO Competition challenges the best power engineers, mathematicians, and computer scientists to make possible operational decisions based on accurate physical models. To accomplish this, the GO Competition created a series of Challenges and funded teams to produce the best solver. Challenge 1 was to solve the security constrained Alternating Current Optimal Power Flow (ACOPF) problem. Challenge 2 extended that to by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and loads, and fast-start unit commitment (UC). Furthermore, Challenge 2 was a maximization problem while Challenge 1 was a minimization problem. While Challenge 3 was being developed, the entrants were invited to find better solutions to the Challenge 2 synthetic datasets with no restrictions on time, hardware, or algorithms. The Challenge 2 solutions turned out to be very good. Challenge 3 expanded the Challenge 2 problem further by using multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead. These problems included active bid-in demand and topology optimization. Together the Challenges used nearly 30 million CPU hours. Since each team was working on the same problem, using the same data, and running on the same hardware, fair comparisons could be drawn as to the best solver. The datasets were varied enough, however, that the best solver for one dataset was not necessarily the best at another, so cumulative scores were used. The process was managed by the PNNL maintained website https://GOCompetition.energy.gov, where Entrants could find information about the problem, the data, the rules, submit their solver for evaluation, and see the scores of all the competing teams on a Leaderboard. Interest was world-wide but only American teams were eligible for prizes. The Competition has produced 34 journal articles 115 papers and been cited over 500 times in the literature, including 12 dissertations (4 from foreign countries; Columbia (2), Germany, and Italy) and 3 from the DOE ExaScale project. Software developed by Pearl Street Technologies for Challenges 1 and 2 is now deployed by Southwest Power Pool (SPP) and Midcontinent Independent Service Operator (MISO). Other teams have received inquiries from venture capitalists. Google DeepMind has thanked the Competition for making the datasets developed for the Competition public. They are using it to train machine learning models. The larger datasets have billions of unknowns to be solved for, but only a small percent matter in the final solution. Knowing what unknowns are important can dramatically speedup the solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Modeling Predictive Maintenance for NuScale’s Condensate and Feedwater System Using EMRALD

Event Modeling Risk Assessment using Linked Diagrams (EMRALD) is used to model of NuScale’s feedwater and condenser system to capture component degradation and repairing process. To model the reliability of the components, a three-stage failure rate is used contrary to a constant rate leading to component failure. Results from EMRALD will be used to compare different maintenance strategies to reduce system downtime. The outcome of the project will assist in maximizing remaining useful life of the overall system and increasing the availability and revenue of the plant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Split HPWHs as an Efficient Solution for Multifamily Buildings with In-Unit Water Heaters: Preprint

A quarter of all housing units in the country are found in multifamily buildings but few efficiency innovations have been made to improve electric water heating systems in this building type. Domestic hot water in multifamily buildings can either be provided by a large central water heater or smaller in-unit water heaters. Integrated heat pump water heaters that are installed in single family homes are often a poor fit for individual multifamily units since the water heaters are often located in small internal closets. This confined space can limit the air flow to the heat pump and the cold exhaust air can cause discomfort and reduced efficiency. Split CO2 HPWHs separate the tank from the heat pump, which allows for installation location flexibility. Further, CO2 heat pumps can operate under colder ambient conditions, making them a better fit for multifamily units across a wide range of climate regions. As part of a larger project to characterize split HPWH performance, we evaluated the feasibility of installing an additional, parallel tank that could provide hot water to a second housing unit using a single CO2 heat pump. This approach would reduce the first costs of these more expensive units. Based on the high draw volume that we imposed on both tanks, the same heat pump may be able to support more tanks, depending on hot water usage. This paper will describe the split CO2 HPWH technology, how the two-tank system was controlled, and results from our laboratory evaluation.

CO2 HPWH↗
DOE OSTI2025

Ultra-low magnetization and hysteresis loss in APC Nb 3 Sn superconductors

For the accelerator magnets of the next hadron collider, reducing superconductor persistent-current magnetization is not only important for achieving the desired field quality, but also crucial for its sustainability because the magnetization loss is the major heat load to the magnet cold mass. For conventional Nb 3 Sn conductors this requires reduction of effective subelement size (D eff ). For the restacked-rod-process (RRP ® ) conductors a physical subelement size (D sub ) as small as 35 µm (corresponding to a D eff close to 45 µm) can be reached, but at a significant price in J c . Another way to reduce the magnetization is by introducing artificial pinning centers (APC) using the internal oxidation approach. APC conductors outperform conventional Nb 3 Sn wires in two aspects: 1) higher J c at high fields, and 2) much lower J c and magnetization at low fields (e.g. below 5 T). Here, in this work we explored the fabricability of APC wires with small D sub . A 180-stack APC wire was produced and drawn to 0.7- and 0.5 mm diameters with good quality, with D sub s of 34 and 24 µm (D eff s of 36 and 25 µm), respectively. For the 34 µm-D sub wire, its non-Cu J c is higher than that of an RRP ® wire used for the High-Luminosity Large Hadron Collider (HL-LHC) project above 13 T (e.g. 36% higher at 4.2 K, 18 T), while its non-Cu magnetization at 1 T, ΔM(1 T), is only 29% of the RRP ® wire. Its non-Cu hysteresis loss for a cycle between 1 and 14 T, Q h (1–14 T), is 37% of the RRP ® wire. For the 24 µm-D sub wire, its non-Cu J c surpasses the HL-LHC RRP ® wire above 17.5 T, while its ΔM(1 T) and Q h (1–14 T) are only 17% and 23% of the RRP® wire, respectively. Its non-Cu Q h (±3 T) even meets the specification of the International Thermonuclear Experimental Reactor project.

Xu, X [Fermi National Accelerator Laboratory (FNAL↗
DOE OSTI2025

Unification of finite symmetries in the simulation of many-body systems on quantum computers

Symmetry is fundamental in the description and simulation of quantum systems. Leveraging symmetries in classical simulations of many-body quantum systems can result in significant overhead due to the exponentially growing size of some symmetry groups as the number of particles increases. Quantum computers hold the promise of achieving exponential speedup in simulating quantum many-body systems; however, a general method for utilizing symmetries in quantum simulations has not yet been established. In this work, we present a unified framework for incorporating symmetry group transforms on quantum computers to simulate many-body systems. The core of our approach lies in the development of efficient quantum circuits for symmetry-adapted projection onto irreducible representations of a group or pairs of commuting groups. We provide resource estimations for common groups, including the cyclic and permutation groups. Our algorithms demonstrate the capability to prepare coherent superpositions of symmetry-adapted states and to perform quantum evolution across a wide range of models in condensed-matter physics and ab initio electronic structure in quantum chemistry. Specifically, we execute a symmetry-adapted quantum subroutine for small molecules in first-quantization on noisy hardware and demonstrate the emulation of symmetry-adapted quantum phase estimation for preparing coherent superpositions of quantum states in various irreducible representations of a symmetry group. In addition, we present a discussion of open problems regarding treating symmetries in digital quantum simulations of many-body systems, paving the way for future systematic investigations into leveraging symmetries quantumly for practical quantum advantage. The broad applicability and rigorous resource estimation for symmetry transformations make our framework appealing for achieving provable quantum advantage on fault-tolerant quantum computers, especially for symmetry-related properties.

quantum algorithms↗
DOE OSTI2020

Mixing-Controlled CI Combustion and Fuel-Effects Research

This project is focused on developing advanced combustion strategies for mixing-controlled compressionignition (i.e., diesel-cycle) engines that are synergistic with renewable and/or unconventional fuels in a manner that enhances domestic energy security, economic competitiveness, and environmental quality. During this reporting period, the focus was on ducted fuel injection (DFI), a technology that differs from conventional diesel combustion (CDC) in that it involves injecting fuel along the axis of one or more small cylindrical ducts within the combustion chamber. Each duct performs a function similar to the tube on a Bunsen burner, helping to premix the fuel with the charge-gas before ignition, creating a stable flame that forms little to no soot. The purpose of the work conducted during Fiscal Year (FY) 2019 was to begin determining the extent to which the use of oxygenated fuels, when combined with DFI and charge-gas dilution, can simultaneously lower the soot and nitrogen-oxides (N0 x ) emissions from mixing-controlled compression-ignition engines, and what the corresponding impacts on other regulated emissions and efficiency are likely to be.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Efficiency of Room Air Cleaners for Removal of Bioaerosols From Ambient Air

The COVID-19 pandemic necessitated the evaluation of commercial air purification units to protect worker safety in indoor spaces. This project evaluated the efficacy of commercial off-the-shelf air purification systems that utilize electrostatic precipitation for the collection and removal of particulates (including bioaerosols) from ambient air. An aerosol mist containing Escherichia coli (E. coli) and bacteriophage surrogate virus, MS2, was produced using a nebulizer and delivered to the front intake of the commercial system with the ionizer ON and OFF. Removal efficiency was evaluated by colony/plaque formation assays using a small agar plate (60 X 15 mm) to passively collect E. coli and MS2 exhausting from the electrostatic precipitation cell. The system was determined to remove 98-99% of the microorganism introduced to the system. Testing was performed with all pre- and post-electrostatic cell filters removed so further removal is anticipated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Completion of initial reduced-order model for flammable refrigerant dispersal in residential spaces

Environmental regulations aimed at reducing global warming impacts of HVAC&R refrigerants have resulted in the phase-out of chlorofluorocarbons (CFCs) in 2010 and hydrochlorofluorocarbons (HCFCs) by 2030 in developed countries with additional restrictions on the use of hydrofluorocarbons (HFCs) set to take effect in 2036. Many of the remaining alternative refrigerants that have lower global warming potential (GWP) and that are suitable for use in HVAC&R systems (e.g., propane, difluoromethane) are flammable to some degree. Flammable refrigerants introduce new challenges and hazards to property and personal safety related to potential deflagration during system maintenance or due to leakage of the refrigerant accumulating in the conditioned space. Standards have been developed to set maximum charge limits for flammable refrigerants in HVAC&R systems; however, existing safety standards and codes still restrict their use. The bodies that maintain and update these codes need publicly available, science-based information to enable credible guidelines for setting safe charge limits for different flammable refrigerants in different HVAC&R applications. In 2016, the Alliance for Responsible Atmospheric Policy, the Air-Conditioning Heating and Refrigeration Institute (AHRI), ASHRAE, the U.S. Department of Energy (DOE), and the State of California began efforts to develop such information. As part of this effort, Oak Ridge National Laboratory (ORNL) began the current, ongoing project to examine imposed charge limits for flammable refrigerants and identify reasonable adjustments to these limits when found appropriate. Past tasks under this project have included development of experimentally vetted, computational fluid dynamics (CFD) simulation approaches to study the results of leakage of flammable refrigerants from various HVAC&R systems into different types of commercial and residential spaces. In this report, we discuss recent efforts to develop a predictive model of the flammable volume fraction and accumulated refrigerant mass in a single-room residential space resulting from the leak of a flammable refrigerant from a small room air conditioning (RAC) unit. The eventual goal is development of a model suitable for public release which could simulate a range of scenarios. In discussions with the AHRTI Flammable Refrigerant Subcommittee (FRS) at the beginning of this effort, a total of 9 input parameters were chosen for consideration including room area, room/door opening area, ventilation fan flow rate, unit/leak height, leak area, leak rate, total refrigerant charge, refrigerant molecular weight, and state of the unit fan.

42 ENGINEERING↗
DOE OSTI2022

Hybrid Hydraulic-Electric Architecture (HHEA) for Mobile Machines (Final Report)

Traditionally, off-road mobile machines such as excavators and wheel loaders are primarily powered by hydraulics, and throttling valves are used to control their work circuits. In recent years, two general trends are towards more energy efficient systems and electrification. With electrification, both efficiency and control performance can be improved by the elimination of throttling losses and the use of high-bandwidth inverter control. Electrification is generally accomplished with Electro-hydraulic actuators (EHA) but they are limited to lower powered systems due to the high cost of electric machines capable of high power or high torque. This project proposes a new system architecture for off-road vehicles - Hybrid Hydraulic Electric Architecture (HHEA) to improve efficiency and control performance without requiring large electric machines. The widely applicable architecture combines hydraulic power and electric power in such a way that the majority of power is provided hydraulically while electric drives are used to modulate this power. In particular, HHEA utilizes multiple common pressure rails to transmit the majority of power and small electric machines to modulate the power. The energy-saving potential of the the HHEA has been validated for the work circuits of a variety of mobile machines, from small 5-ton excavators to medium sized 20-ton excavators and wheel loaders, and representative duty cycles to reduce energy input by 50-80% compared to the commercial state-of-art load-sensing systems. In addition, the corner power requirements of the electrical machines can be downsized by 85% compared to the EHA approach. Various tradeoff studies have also been conducted, including sensitivities to individual components performances, controllers, accumulator sizes, and variations of the system architecture etc. A control strategy has been developed to maintain or exceed the motion control precision compared to current systems. The motion control strategy consists of a nominal controller, based on a passivity-based backstepping design, and a transition controller, based on least-norn feedforward design. The nominal controller is used in between common pressure rail switches whereas the transition controller compensates for any disturbance that common pressure rail switchings inflict on the system. The control strategy has been experimentally validated on both a medium pressure (200bar) hardware-in-the-loop (HIL) testbed and a high pressure (300+bar) HIL testbed. An efficient and power-dense integrated electric-hydraulic machine consisting of an axial flux electric machine and a radial hydrostatic piston hydraulic machine has been designed, constructed and tested. The machine has an active material power density of 6.1kW/kg, a rated speed of 12500 RPM, and a design efficiency of 85%. This is among the highest power density electric machines using conventional materials. While the integrated machine was designed for modulating the hydraulic power within the HHEA, it can also be used in other applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Statistical Learning for Nonlinear Model Reduction from Local Simulations of Stochastic and Particle- and Agent-Based Systems

Stochastic physical systems across the sciences that have very high-dimensional state spaces, with a large number of fast degrees of freedom that force direct simulators to proceed by integration steps that are orders of magnitude smaller than events of interests (e.g., particle collisions). Examples range from molecular motion to dynamics of large populations of cells. A grand challenge in the simulation and understanding of such systems is the systematic construction of accurate, interpretable, reduced models, enabling faster simulations, revealing fundamental properties of the dynamics, and predicting phenomena of interest that the original simulator could not reached with sufficient accuracy or within a given computational budget. In this projected we developed novel statistical estimation/machine learning techniques for analyzing and building empirical reduced models for important families of high-dimensional stochastic systems, in particular: - we developed techniques for estimating interaction kernels in interacting particle- and agent-based systems, which are ubiquitous in Physics, Biology and many other sciences, given observed trajectories of the system; - we developed techniques for nonlinear model reduction for high-dimensional stochastic systems that have a small number of unknown, nonlinear slow variables, and a large number of fast modes, that are possibly of large magnitude, given observed short trajectories of the system in the form of bursts of trajectories from different initial conditions; - we developed novel techniques for estimating linear dynamical systems on graphs when both the dynamics and the underlying graph are unknown, and we have a sparse set of space-time observations; - we considered the problem of estimating an unknown nonlinear observation function of a standard process (e.g. Brownian motion), so that we can recognized if an observed dynamics is "just" a nonlinear version of a known dynamics; we also developed benchmarks for learning algorithms aimed at learning and classifying diffusion processes.

97 MATHEMATICS AND COMPUTING↗