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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrated Spatial, Spectral, & Temporal Optical Reflectance System for Precision Occupancy & Location Sensing to Improve Building Energy Efficiency

Buildings consume approximately 35% of the electricity used in the U.S. and building owners can significantly reduce this energy use by providing services like heating, electrical power and lighting only when people are present. The ARPAe funded program titled “INTEGRATED SPATIAL, SPECTRAL, & TEMPORAL OPTICAL REFLECTANCE SYSTEM FOR PRECISION OCCUPANCY & LOCATION SENSING TO IMPROVE BUILDING ENERGY EFFICIENCY” demonstrates how a low cost sensor technology developed for measuring distances can be used to count and locate occupants with a high degree of precision with a very low error rates. This platform tells a building control system where occupants are located (but not who they are) so that energy consuming services can be provided only when the services are needed by building occupants. The original proof of concept involved using low cost, commercially available time-of-flight (TOF) sensors that measure distance, but the performance of these existing sensors was lacking, as they could not operate properly in the presence of sunlight, which blinded the simple TOF sensors and limited their utility in buildings. This project proposed a powerful new class of TOF sensors that used state-of-the-art integrated circuit (IC) fabrication processes that combined advanced photonics with conventional silicon chip circuitry for improved sensor performance. An equally important part of this project was to find ways to maximize occupant count and location accuracy while using the fewest number of sensors possible, in order to keep costs low. By using building blueprints to create digital twins of commercial building spaces, the team developed new algorithms to maximize occupant count and tracking accuracy by properly locating the minimum number of sensors at just the right spots in the building. This capability not only minimizes system costs but also simplified sensor installation and system commissioning. Our simulations of our sensor networks for a range of commercial floorplan designs demonstrated that our installed cost target of $0.08/sqft was attainable, though not fully demonstrated during the project. Finally, we noted that the TOF sensor concept could provide a valuable role in health and eldercare by tracking patients without the need for worn sensors and would be useful for fall detection and other patient safety metrics, including tracking healthcare/patient interactions. We feel that, when fully developed, this new class of sophisticated TOF sensors and support software will be a powerful new approach to improving building energy efficiency based on occupant centric control platforms and will also open new levels of patient safety in healthcare operations. To realize this potential, the team formed the Troy Sensor Company LLC to oversee licensing of the programs patents and continue to seek commercialization of this program’s activity sensing technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts

Adsorbates often cover the surfaces of catalysts densely as they carry out reactions, dynamically altering their structure and reactivity. Understanding adsorbate-induced phenomena and harnessing them in our broader quest for improved catalysts is a substantial challenge that is only beginning to be addressed. Here, in this work, we chart a path toward a deeper understanding of such phenomena by focusing on emerging in silico modeling methodologies, which will increasingly incorporate machine learning techniques. We first examine how adsorption on catalyst surfaces can lead to local and even global structural changes spanning entire nanoparticles, and how this affects their reactivity. We then evaluate current efforts and the remaining challenges in developing robust and predictive simulations for modeling such behavior. Last, we provide our perspectives in four critical areas—integration of artificial intelligence, building robust catalysis informatics infrastructure, synergism with experimental characterization, and adaptive modeling frameworks—that we believe can help surmount the remaining challenges in rationally designing catalysts in light of these complex phenomena.

catalytic mechanisms↗
DOE OSTI2020

GADRAS Batch Inject Tool User Guide

Gamma Detector Response and Analysis Software (GADRAS) is used by the radiation detection and emergency response community to perform modeling and spectral analysis for gamma detector systems. Built into GADRAS is the ability to define a detector, geometry, background characteristics and source composition to generate synthetic spectra for drills and exercises (injects). Consequence Management is currently in development of a sample result data simulator tool in which a deposition model is probed for source conditions at moments in time and locations in space. These values are used to generate realistic sample results for use in drills and exercises. In addition to sample results, there is a need to simulate the actual spectra that would be observed in the field by downlooking HPGe instruments given a deposition activity. This way, the FRMAC Gamma Spectroscopist can practice their process of generating quantified results from spectra on realistic data as well. Recognizing the decades of work done in GADRAS to accurately generate synthetic spectra, this team decided to build a link between the new simulator and GADRAS to generate these spectra quickly and easily. The simulator tool will generate a file that specifies the name of the spectra, its location, date/time of measurement, duration of measurement, height off the ground, and the deposition activity and age for every radionuclide in the simulation. Then, a new tool within the Inject Tab of GADRAS was developed to read in this file given a detector selection and generate In-Situ spectra for each row in the file in any file format the user chooses. This way, simulation cell staff can take these files and then upload them to the appropriate data system (RAMS or RadResponder) for use during drills and exercises. An advanced feature of this tool allows for generating any spectra given an appropriate model and mapping of source to model layer in the batch inject tool. This way, spectra from field sample counts, mobile laboratories, or even fixed laboratories can be generated in bulk given an estimate of the radioactivity concentration or total radioactivity in an import file. This expands the capabilities of this tool a great deal and will make it a more useful tool for CM and others to help estimate detector response for nearly any situation. This user guide will explain the steps needed to perform a batch inject file generation.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Human‐Skin‐Inspired Adaptive Smart Textiles Capable of Amplified Latent Heat Transfer for Thermal Comfort

Thermally adaptive textiles (TATs) enable human subjects to attain thermal comfort without energy consumption, which can lead to enormous energy savings on heating, ventilation, and air conditioning (HVAC) in buildings. Herein, TAT structures which respond to the sweat and generate pores by opening an array of flap‐shaped pores patterned on the fabric surface are proposed. A moisture‐driven self‐actuator for flap opening by constructing a bilayer consisting of a hygroscopic layer using polyethylene glycol and cellulose acetate, and a hydrophobic polymer using a polyester type polymer, is used and successfully demonstrated an essentially instant 4 °C apparent temperature cooling performance within one minute of sweat–humidity‐initiated actuation while wearing TAT using a sweating skin simulated device.

Kim, Gunwoo↗
DOE OSTI2025

Dual-season thermal energy storage-integrated heat pump system for load shifting: experiments, modeling and nationwide analysis

Here, this paper proposes and validates a dual-season thermal energy storage-integrated heat pump (TES-HP) system that shifts building electric load in both cooling and heating modes using a single phase-change TES. The design uses the TES as a heat sink for the condenser in summer and a heat source for the evaporator in winter, thereby reducing on-peak electric demand while ensuring compatible with existing air-distribution systems. A 14-kW TES-HP prototype with six operating modes and novel refrigerant charge management strategies was experimentally tested under varied conditions. Subsequently, data-driven polynomial performance curves were developed and validated against experiments, then coupled with a phase change material (PCM) model and a calibrated building model within a rule-based controller. Single-day case studies demonstrated effective on-peak demand reduction while maintaining thermal comfort. During cooling, hourly power was lowered by up to 1.5 kW; in heating, average hourly power decreased from over 3.5 kW to 1.8 kW, compared to an HP-only system, achieving 64.5 % load shifting, and the need for resistance heating was eliminated. Seasonal simulations showed typical on-peak electricity savings of 25–35 % in cooling and 40–65 % in heating, with the largest benefits on the hottest and coldest days. Extended response-surface analysis and nationwide mapping quantified load shifting as functions of ambient and TES temperatures, revealing a seasonal trade-off in TES phase-change temperature. These results demonstrate the TES-HP system as a practical and scalable solution for grid-interactive buildings that reduces on-peak demand and electricity use while maintaining thermal comfort and enhancing grid flexibility and reliability.

Grid-interactive buildings↗
DOE OSTI2020

Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration

Model predictive control (MPC) has been proven in simulations and pilot case studies to be a superior control strategy for large buildings. MPC can utilize the weather and occupancy schedule forecasts, together with the system model, to predict the future thermal behavior of the building and minimize the overall energy use and maximize thermal comfort. However, these advantages come with the cost of increased modeling effort, computational demands, communication infrastructure, and commissioning efforts. Thus a typical approach is to, often rapidly, simplify the building modeling and MPC optimization problem while paying a price of not reaching the full performance potential. It has been shown that by employing accurate physics-based models, MPC performance can be notably increased closer to its theoretical performance bound. However, implementation of such high-fidelity MPC in real buildings remains a challenge, resulting in a lack of successful field test studies. This work presents the methodology and field test demonstration of a computationally efficient implementation of the white-box MPC in an office building in Belgium. The detailed model of the building is based on first-principle physical equations. The deployment and supervision of MPC operation in a practical setting are supported by an automated cloud-based communication infrastructure. The motivating factor behind the cloud-based architecture is its compatibility with a commercially appealing control as a service concept. The building is equipped with a ground source heat pump (GSHP) and thermally activated building structures (TABS), where the combination of both is also known as GEOTABS. From a control perspective, GEOTABS buildings are particularly challenging systems due to large scale, complex heating, ventilation and air conditioning (HVAC) system, and slow dynamics with time delays. On the other hand, there is an increased potential for energy savings due to the high thermal mass, which acts as thermal storage. The MPC operation is demonstrated during the challenging transient seasons (switching between heating and cooling), and its performance is compared to a traditional rule-based controller (RBC). We provide a proof of concept of real MPC operation for the most difficult seasons with notable GSHP energy use savings equal to 53.5% and thermal comfort improvement by 36.9%. Other MPC applications found in the literature describe tests for only cooling or only heating, and up to now only for a black-box or a grey-box approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Calibration strategy of the PROSPECT-II detector with external and intrinsic sources

This paper presents an energy calibration scheme for an upgraded reactor antineutrino detector for the Precision Reactor Oscillation and Spectrum Experiment (PROSPECT). The PROSPECT collaboration is preparing an upgraded detector, PROSPECT-II (P-II), to advance capabilities for the investigation of fundamental neutrino physics, fission processes and associated reactor neutrino flux, and nuclear security applications. P-II will expand the statistical power of the original PROSPECT (P-I) dataset by at least an order of magnitude. The new design builds upon previous P-I design and focuses on improving the detector robustness and long-term stability to enable multi-year operation at one or more sites. The new design optimizes the fiducial volume by elimination of dead space previously occupied by internal calibration channels, which in turn necessitates the external deployment. In this paper, we describe a calibration strategy for P-II. Here, the expected performance of externally deployed calibration sources is evaluated using P-I data and a well-benchmarked simulation package by varying detector segmentation configurations in the analysis. The proposed external calibration scheme delivers a compatible energy scale model and achieves comparable performance with the inclusion of an additional AmBe neutron source, in comparison to the previous internal arrangement. Most importantly, the estimated uncertainty contribution from the external energy scale calibration model meets the precision requirements of the P-II experiment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Koopman Model Predictive Control for Eco-Driving of Automated Vehicles

In this paper, we develop a data-driven process for building a model predictive control (MPC) for eco-driving of automated vehicles. The process involves performing system identification in which the non-linear vehicle dynamics model is approximated by the Koopman operator, a linear predictor of higher state-dimension, in a data-driven framework. This approach allows us to formulate the eco-driving problem in a constrained quadratic program that leads to a computationally fast MPC. The MPC is then implemented as a closed-loop control of an electric vehicle in numerical simulations for demonstration.

autonomous vehicle↗
DOE OSTI2025

Genetic algorithm optimization of nuclear criticality experiment for reduction of intermediate-energy 239 Pu nuclear data uncertainties

Nuclear criticality experiments are conducted to investigate specific nuclear data important for safe handling and storage of fissile materials, reactor design and operation, and the validation of radiation transport codes. Incorrect or uncertain nuclear data can prohibitively impact operational safety limits, reactor licensing, and predictive simulation capability; therefore, integral measurements from criticality experiments are necessary and should be performed frequently. To maximize the impact of the integral measurements, it is important to consider experiment geometry, material selection, and component dimensions. When taking these considerations into account, the experiment design process becomes iterative and very time intensive. This work utilizes a genetic algorithm to efficiently explore potential nuclear criticality experiment designs for the Laboratory Directed Research & Development project PARADIGM (PARallel Approach of Differential and InteGral Measurements) at Los Alamos National Laboratory. In this paper, the building blocks of the genetic algorithm are discussed in detail, the genetic algorithm methodology is verified, and the genetic algorithm is used to produce three candidate experiment models for the final PARADIGM design. The three candidate models produced by the genetic algorithm consist of copper-reflected assemblies containing 14 repeating units of alumina, graphite, boron, and plutonium plates. Furthermore, in addition to the optimization results, final design considerations are also discussed for designs with a height and/or weight very close to or slightly above assembly machine operational limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Development and validation of fully open-source R2S shutdown dose rate capabilities in OpenMC *

We present the first fully open-source capabilities for shutdown dose rate (SDR) calculations of fusion energy facilities based on the Rigorous 2-Step (R2S) methodology. These capabilities have been implemented in the OpenMC Monte Carlo particle transport code, building on its existing capabilities while also leveraging new features that have been added to the code to support SDR calculations, such as decay photon source generation. Each of the individual physics components in the R2S workflow—neutron transport, activation, decay photon source generation, and photon transport—have been verified through code-to-code comparisons with MCNP6.2 and FISPACT-II 4.0. These comparisons generally demonstrate excellent agreement between codes for each of the physics components. The full cell-based R2S workflow was validated by performing a simulation of the first experimental campaign from the Frascati Neutron Generator (FNG) ITER dose rate benchmark problem from the Shielding INtegral Benchmark Archive and Database (SINBAD). For short cooling times, the dose calculated by OpenMC agrees with the experimental measurements within the stated experimental uncertainties. For longer cooling times, an overprediction of the shutdown dose was observed relative to experiment, which is consistent with previous studies in the literature. Altogether, these features constitute a combination of capabilities in a single, open-source codebase to provide the fusion community with a readily-accessible option for SDR calculations and a platform for rapidly analyzing the performance of fusion technology.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Feasibility of fusion plasma burn control via real-time, sub-divertor neutral gas isotopic and compositional analysis

The ability to provide fusion burn control without requiring physical access through the first wall and fuel breeding blankets, would be vital for any future, magnetically confined fusion power reactor. A multi-sensor, fusion fuel cycle exhaust, neutral gas analysis system on JET, capable of delivering real time data, and accessing only the sub-divertor region, provides an excellent example of such capability. Optimized for and operated during the deuterium–tritium experimental campaigns 2 and 3 (DTE2, DTE3), it is proving valuable for planning to explore fusion reactor burn control in ITER with a comparable diagnostic system called the Diagnostic Residual Gas Analyzer (DRGA). This paper aims to show feasibility of developing model-based controllers for ITER and next generation, reactor-relevant devices, by building both on the empirical experience in JET-DTE2, and on the already emerging experience on developing such models specifically for ITER. The paper begins with a specific use-case from JET-DTE2, pertaining to the observed sensitivity of the fusion neutron yield on the concentration of isotopic helium-3 ( 3 He), with data from one of the high-performance DT shots exhibited with emphasis on the 3 He measurement via the sub-divertor. Then, a first model is developed and then explored with simulations that aim to discover how well the controllers in the model react to either insufficient levels of 3 He or excessive levels of 3 He. The simulations then explore potential impact from a delay in the measurement (or the response) that would be comparable to the ∼1 s, conductance limited response for the ITER DRGA system, currently in its final design. The simulations show that control is feasible, and that its effectiveness is not significantly impacted by such delay.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Cabana: A Performance Portable Library for Particle-Based Simulations

Particle-based simulations are ubiquitous throughout many fields of computational science and engineering, spanning the atomistic level with molecular dynamics (MD), to mesoscale particle-in-cell (PIC) simulations for solid mechanics, device-scale modeling with PIC methods for plasma physics, and massive N-body cosmology simulations of galaxy structures, with many other methods in between (Hockney & Eastwood, 1989). While these methods use particles to represent significantly different entities with completely different physical models, many low-level details are shared including performant algorithms for short- and/or long-range particle interactions, multi-node particle communication patterns, and other data management tasks such as particle sorting and neighbor list construction. Cabana is a performance portable library for particle-based simulations, developed as part of the Co-Design Center for Particle Applications (CoPA) within the Exascale Computing Project (ECP) (Alexander et al., 2020). The CoPA project and its full development scope, including ECP partner applications, algorithm development, and similar software libraries for quantum MD, is described in (Mniszewski et al., 2021). Cabana uses the Kokkos library for on-node parallelism (Edwards et al., 2014; Trott et al., 2022), enabling simulation on multi-core CPU and GPU architectures, and MPI for GPU-aware, multi-node communication. Cabana provides particle simulation capabilities on almost all current Kokkos backends, including serial execution, OpenMP (including OpenMP-Target for GPUs), CUDA (NVIDIA GPUs), HIP (AMD GPUs), and SYCL (Intel GPUs), providing a clear path for the coming generation of accelerator-based exascale hardware. Cabana builds on Kokkos by providing new particle data structures and particle algorithms resulting in a similar execution policy-based, node-level programming model that is intended to be used in addition to the core Kokkos library within an application. Cabana is designed as an application and physics agnostic, but particle-specific toolkit which can either be used to generate a new application, or to be used as needed in existing applications at various levels of invasiveness including through interfaces that wrap user memory in existing data structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Development of a Test-Bed for Testing and Refining EarthEn’s Supercritical CO 2 Based Energy Storage System

EarthEn’s energy storage concept leverages supercritical carbon dioxide (sCO 2 ) as a working fluid and relies on compact, high-performance components operating at elevated pressures and temperatures. To accelerate component development and reduce technical risk prior to larger-scale demonstrations, Oak Ridge National Laboratory (ORNL) developed a 100 kW-scale sCO 2 test-bed under a Cooperative Research and Development Agreement with EarthEn (CRADA NO. NFE-24-10050). The objective of the work was to design and construct a flexible experimental facility capable of reproducing key thermodynamic state points and heat-transfer conditions relevant to EarthEn’s thermal energy storage (TES) cycle, with particular emphasis on enabling development and evaluation of next-generation heat exchangers and TES concepts. The test-bed consists of a closed-loop sCO 2 circulation system housed within an open-topped enclosure. In its as-installed configuration, dense-phase sCO 2 is recirculated through a printed circuit recuperator, an electrically heated section, a throttling device used to simulate turbine expansion, and a water-cooled printed circuit heat exchanger that rejects heat to the building chilled-water system before returning to the pump. The pump is driven by a variable frequency drive, enabling controlled adjustment of flow and operating point. A comprehensive instrumentation suite was integrated to support both safe operation and high-quality data collection. Installed sensors include Coriolis flow meters for sCO 2 flow rate and density, resistance temperature detectors and thermocouples distributed throughout the loop (including the heated section and key heat exchanger ports), and pressure transducers for absolute and differential pressure measurements. The facility was designed to support high-pressure (19 MPa nominal) and high-temperature (575°C nominal) operation with credited overpressure protection provided by a rupture disk. Nominal operating conditions were selected to support 100 kW-class testing while maintaining flexibility for non-heated and heated shakedown, control development, and future integration of advanced TES test sections. In parallel with facility development, a system-level thermal-hydraulic model was created using Modelica-based tools to support component sizing, anticipate performance over targeted test conditions, and establish a framework for future model calibration against experimental data. At the conclusion of the project performance period, the facility was in final assembly, and the pressure boundary was nearly completed. However, several practical challenges associated with high-pressure/high-temperature systems and specialized component procurement impacted schedule and prevented initial pump-driven operation and full commissioning within the available resources. This report documents the as-built design, operating capabilities, and instrumentation, and it summarizes key lessons learned related to heater fabrication and testing, first-of-a-kind assembly factors, specialty flange supply constraints, and fill pump corrective actions. Finally, it outlines a phased plan for future commissioning and experimental campaigns, including control and instrumentation shakedown, heater characterization, model calibration, and testing at state points representative of EarthEn’s TES cycle.

25 ENERGY STORAGE↗
DOE OSTI2023

Chapter 6: Abuse Response of Batteries Subjected to Mechanical Impact

Electrochemical and thermal models to simulate nominal performance and abuse response of lithium-ion cells and batteries have been reported widely in the literature. Studies on mechanical failure of cell components and how such events interact with the electrochemical and thermal response are relatively less common. This chapter outlines a framework developed under the Computer Aided Engineering for Batteries program to couple failure modes resulting from external mechanical loading to the onset and propagation of electrochemical and thermal events that follow. Starting with a scalable approach to implement failure criteria based on thermal, mechanical, and electrochemical thresholds, we highlight the practical importance of these models using case studies at the cell and module level. The chapter also highlights a few gaps in our understanding of the comprehensive response of batteries subjected to mechanical crash events, the stochastic nature of some of these failure events, and our approach to build safety maps that help improve robustness of battery design by capturing the sensitivity of some key design parameters to heat generation rates under different mitigation strategies.

abuse simulations↗
DOE OSTI2025

Introducing GPU Acceleration into the Python-Based Simulations of Chemistry Framework

We introduce the first version of GPU4P Y SCF, a module that provides GPU acceleration of methods in P Y SCF. As a core functionality, this provides a GPU implementation of two-electron repulsion integrals (ERIs) for contracted basis sets comprising up to g functions using the Rys quadrature. As an illustration of how this can accelerate a quantum chemistry workflow, we describe how to use the ERIs efficiently in the integral-direct Hartree–Fock build and nuclear gradient construction. Benchmark calculations show a significant speedup of 2 orders of magnitude with respect to the multithreaded CPU Hartree–Fock code of P Y SCF and the performance comparable to other open-source GPU-accelerated quantum chemical packages, including GAMESS and QUICK, on a single NVIDIA A100 GPU.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Beyond mass: detecting secondary halo properties with galaxy-galaxy lensing

ABSTRACT Secondary halo properties beyond mass, such as the mass accretion rate (MAR), concentration, and the half mass scale, are essential in understanding the formation of large-scale structure and dark matter haloes. In this paper, we study the impact of secondary halo properties on the galaxy-galaxy lensing observable, ΔΣ. We build an emulator trained on N-body simulations to model ΔΣ and quantify the impact of different secondary parameters on the ΔΣ profile. We focus on the impact of MAR on ΔΣ. We show that a 3σ detection of variations in MAR at fixed halo mass could be achieved with the Hyper Suprime Cam survey assuming no baryonic effects and a proxy for MAR with scatter <1.5. We show that the full radial profile of ΔΣ depends on secondary properties at fixed halo mass. Consequently, an emulator that can perform full shape fitting yields better than two times improvement upon the constraints on MAR than only using the outer part of the halo. Finally, we highlight that miscentring and MAR impact the radial profile of ΔΣ in a similar fashion, implying that miscentring and MAR need to be modelled jointly for unbiased estimates of both effects. We show that present-day lensing data sets have the statistical capability to place constraints on halo MAR within our assumptions. Our analysis opens up new possibilities for observationally measuring the assembly history of the dark matter haloes that host galaxies and clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Practical Introduction to Benchmarking and Characterization of Quantum Computers

Rapid progress in quantum technology has transformed quantum computing and quantum information science from theoretical possibilities into tangible engineering challenges. Breakthroughs in quantum algorithms, quantum simulations, and quantum error correction are bringing useful quantum computation closer to fruition. These remarkable achievements have been facilitated by advances in quantum characterization, verification, and validation (QCVV). QCVV methods and protocols enable scientists and engineers to scrutinize, understand, and enhance the performance of quantum information-processing devices. In this tutorial, we review the fundamental principles underpinning QCVV, and introduce a diverse array of QCVV tools used by quantum researchers. We define and explain QCVV’s core models and concepts—quantum states, measurements, and processes—and illustrate how these building blocks are leveraged to examine a target system or operation. We survey and introduce protocols ranging from simple qubit characterization to advanced benchmarking methods. Along the way, we provide illustrated examples and detailed descriptions of the protocols, highlight the advantages and disadvantages of each, and discuss their potential scalability to future large-scale quantum computers. This tutorial serves as a guidebook for researchers unfamiliar with the benchmarking and characterization of quantum computers, and also as a detailed reference for experienced practitioners.

open quantum systems & decoherence↗
DOE OSTI2022

EXPERIMENTAL AND MODELLING ANALYSIS OF A LARGE-SCALE TWO-PHASE LOOP THERMOSYPHON

Liquid pumping requires large quantities of electrical energy, including about 7% of the energy of building heating, ventilation, and air conditioning (HVAC) systems. To replace pumped condenser-cooling tower water loops with a passive alternative system, we implemented a commercial-scale two-phase loop thermosyphon (TPLT). The unit consists of a 13 m riser integrated with a commercially available cooling tower and circulation water heater that simulates heat loads up to 25 kW. In addition to providing passive cooling capabilities, the cooling tower unit is also maintenance free, reliable, and can operate in both dry and wet modes. This study characterizes the performance (temperature difference between the evaporator and condenser) and the two-phase flow behavior of the loop under various refrigerant charges. Sight glasses installed throughout the loop are used to identify the operating flow regimes in the riser and downcomer. Over the range of operating conditions, we identified that there is an optimal refrigerant charge range for a specific heat load at which near-isothermal operation can be achieved. We further developed a model to predict the operating flow rate and gravitational height in the downcomer and compared it with the experimental data. The results show that the model agrees with the experimental data, in particular the threshold gravitational head height at which there will be subcooled liquid at the condenser exit, indicating that it can be used as a predictive tool for identifying the optimal loop charge for a given heat load.

Loop thermosyphon, passive two phase↗