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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

On mechanical waves and Doppler shifts from moving boundaries

We investigate the propagation of infinitesimal harmonic mechanical waves emitted from a boundary with variable velocity and arriving at a stationary observer. In the classical Doppler effect, X s (t)=vt is the location of the source with constant velocity v. In the present work, however, we consider a source co-located with a moving boundary x=X s (t), where X s (t) can have an arbitrary functional form. For ‘slowly moving’ boundaries (i.e., ones for which the timescale set by the mechanical motion is large in comparison to the inverse of the frequency of the emitted wave), we present a multiple-scale asymptotic analysis of the moving boundary problem for the linear wave equation. Here, we obtain a closed-form leading-order (with respect to the latter small parameter) solution and show that the variable velocity of the boundary results not only in frequency modulation but also in amplitude modulation of the received signal. Consequently, our results extend the applicability of two basic tenets of the theory of a moving source on a stationary domain, specifically that (i) $.\atop{x}_s$ for non-uniform boundary motion can be inserted in place of the constant velocity v in the classical Doppler formula and (ii) that the non-uniform boundary motion introduces variability in the amplitude of the wave. The specific examples of decelerating and oscillatory boundary motion are worked out and illustrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Progress Toward Evaluating Roughness-Resolved Aerothermodynamic Simulations for the Mars Sample Return Earth Entry System

This work pursues the efficient Navier-Stokes simulation, using NASA’s standard LAURA and DPLR simulation tools, of the flowfield and convective heating resulting from the patterned-roughness surface of the Mars Sample Return (MSR) Earth Entry System (EES). This type of simulation has been infeasible for past NASA missions. However, for EES, the combination of a patterned roughness heatshield approximated with a sinusoidal pattern, the zero degrees angle of attack nominal flow, and the supersonic boundary layer edge Mach number, all combine to make these roughness resolved grid simulations feasible. The patterned roughness and zero degrees angle of attack nominal flow allow the simulation domain to be reduced to a thin axial flowfield slice that captures a minimum of single period of the roughness pattern. With a periodic boundary condition applied along the boundaries of this slice, simulation on the reduced domain is identical to the full domain but with significant cost saving. The supersonic boundary layer edge Mach number prevents the upstream influence, which allows the smooth stagnation region to be frozen. This freezing of the stagnation region flow is required because of the numerical instability resulting from the tight spacing of the grid in the axial direction as the stagnation point is approached. Applying the developed analysis approach to a peak heating EES case results in a roughness augmentation factor for the convective heating of 1.32, which agrees well with correlations that predict values between 1.30 and 1.37. Analysis approach developed in this work provides the framework for future studies of turbulence modeling impacts and the influence of an ablating surface.

Earth Entry System↗
NASA NTRS2023

A Synthetic Roman Space Telescope High-Latitude Time-Domain Survey: Supernovae in the Deep Field

NASA will launch the Nancy Grace Roman Space Telescope (hereafter Roman ) in the second half of this decade, which will allow for a generation-defining measurement of dark energy through multiple probes, including Type Ia supernovae (SNe Ia). To impro v e decisions on surv e y strate gy, we hav e created the first simulations of realistic Roman images that include artificial SNe Ia injected as point sources in the images. Our analysis combines work done on Roman simulations for weak gravitational lensing studies as well as catalogue-level simulations of SN Ia samples. We have created a time series of images o v er 2 yr containing ∼1050 SNe Ia, co v ering a 1 deg 2 subarea of a planned 5 deg 2 deep survey. We have released these images publicly for community use along with input catalogues of all injected sources. We create secondary products from these images by generating coadded images and demonstrating reco v ery of transient sources using image subtraction. We perform first-use analyses on these images in order to measure galaxy detection efficiency, point source detection efficiency, and host-galaxy association biases. The simulated images can be found here at https:// roman.ipac.caltech.edu/sims/ SN Survey Image sim.html .

supernovae↗
DOE OSTI2026

On the Trotter Error in Many-body Quantum Dynamics with Coulomb Potentials

Efficient simulation of many-body quantum systems is central to advances in physics, chemistry, and quantum computing, with a key question being whether the simulation cost scales polynomially with the system size. Here, in this work, we analyze many-body quantum systems with Coulomb interactions, which are fundamental to electronic and molecular systems. We prove that Trotterization for such unbounded Hamiltonians achieves a 1/4-order convergence rate, with explicit polynomial dependence on the number of particles. The result holds for all initial wavefunctions in the domain of the Hamiltonian, and the 1/4-order convergence rate is optimal, as previous work has numerically demonstrated that it can be saturated by a specific initial ground state. The main challenges arise from the many-body structure and the singular nature of the Coulomb potential. Our proof strategy differs from prior state-of-the-art Trotter analyses, addressing both difficulties in a unified framework. Our analysis treats the Coulomb potential as an unbounded operator without modification or regularization, and does not rely on spatial discretization, making it compatible with both first- and second-quantized circuit constructions.

Fang, Di [Duke Univ., Durham, NC (United States)]↗
DOE OSTI2015

A general ansatz for constructing quasi-diabatic states in electronically excited aggregated systems

We present a general method for analyzing the character of singly excited states in terms of charge transfer (CT) and locally excited (LE) configurations. The analysis is formulated for configuration interaction singles (CIS) singly excited wave functions of aggregate systems. It also approximately works for the second-order approximate coupled cluster singles and doubles and the second-order algebraic-diagrammatic construction methods [CC2 and ADC(2)]. The analysis method not only generates a weight of each character for an excited state, but also allows to define the related quasi-diabatic states and corresponding coupling matrix elements. In the character analysis approach, we divide the target system into domains and use a modified Pipek-Mezey algorithm to localize the canonical MOs on each domain, respectively. The CIS wavefunction is then transformed into the localized basis, which allows us to partition the wavefunction into LE configurations within domains and CT configuration between pairs of different domains. Quasi-diabatic states are then obtained by mixing excited states subject to the condition of maximizing the weight of one single LE or CT configuration (localization in configuration space). Different aims of such a procedure are discussed, either the construction of pure LE and CT states for analysis purposes (by including a large number of excited states) or the construction of effective models for dynamics calculations (by including a restricted number of excited states). Applications are given to LE/CT mixing in π-stacked systems, charge-recombination matrix elements in a hetero-dimer, and excitonic couplings in multi-chromophoric systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Quantification of Mixed Bloch-Néel Topological Spin Textures Stabilized by the Dzyaloshinskii-Moriya Interaction in Co / Pd Multilayers

The three-dimensional structure of nanoscale topological spin textures stabilized by the Dzyaloshinskii-Moriya interaction is governed by the delicate competition between the exchange, demagnetization, and anisotropy energies. The quantification of such spin textures through direct experimental methods is crucial towards understanding the fundamental physics associated with their ordering, as well as their manipulation in spintronic devices. Here in this work, we extend the Lorentz transmission electron microscopy technique to quantify mixed Bloch-Néel chiral spin textures stabilized by the Dzyaloshinskii-Moriya interaction in Co / Pd multilayers. Analysis of the observed intensities under varied imaging conditions coupled to corroborative micromagnetic simulations yields vital parameters that dictate the stability and properties of the complex spin texture, namely, the degree of mixed Bloch-Néel character, the domain wall width, the strength of the Dzyaloshinskii-Moriya interaction, and the exchange stiffness. In conclusion, this approach provides the necessary framework for the application of quantitative Lorentz phase microscopy to a broad array of topological spin systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Memory-Aware External Facelist Calculation: A Data-Parallel Atomic Hash Counting Approach

Unstructured volumetric meshes serve as fundamental data representations in various scientific simulations and analyses. They play a crucial role in representing complex computational domains and are essential for important numerical techniques, such as finite element analysis. Whenever such a mesh is read from a file, streamed in-situ, or generated by algorithms, scientific visualization libraries rely on calculating the external surface of a geometry, named “external facelist”, to produce a polygonal mesh for rendering. Consequently, external facelist calculation has become one of the most widely used algorithms in the scientific visualization domain, necessitating optimal performance. In this paper, we explore relevant work on external facelist calculation algorithms in two common visualization libraries, VTK and Viskores, assess their performance and memory constraints, and introduce a novel memory-aware external facelist calculation algorithm employing an atomic hash counting approach. This algorithm fully leverages Viskores' data-parallel primitive operations, facilitating its execution across diverse many-core architectures. Our algorithm features the lowest memory footprint on the GPU and the second-lowest on the CPU among all evaluated methods, and it also delivers the fastest performance on both CPU and GPU. It has been made available under an open-source license in the VTK and Viskores visualization systems.

Tsalikis, Spiros [Kitware] (ORCID:0000000151137195↗
DOE OSTI2021

cuTS: Scaling Subgraph Isomorphism on Distributed Multi-GPUSystems Using Trie Based Data Structure

Subgraph isomorphism is a pattern-matching algorithm widely used in many domains such as chem-informatics, bioinformatics, databases, and social network analysis. It is computationally expensive and is a proven NP-hard problem. The massive parallelism offered by the GPU hardware is well suited for solving the subgraph isomorphism. However, current GPU implementations are far from the achievable performance. Moreover, the enormous memory requirement of current approaches limits the problem size that can be handled. This work analyzes the fundamental challenges associated with processing the subgraph isomorphism on GPUs and develops an efficient GPU hardware-aware implementation. We also develop a new GPU-friendly trie-based data structure to drastically reduce the intermediate storage space requirement. Hence, our approach runs larger benchmarks than the competitors. We also develop the first distributed sub-graph isomorphism algorithm for GPUs. Our experimental evaluation section demonstrates the efficacy of our approach by comparing the execution time and number of cases that we can handle against the state-of-the-art GPU implementations.

Xiang, Lizhi↗
DOE OSTI2018

Time and Frequency Domain Methods for Basis Selection in Random Linear Dynamical Systems

Polynomial chaos methods have been extensively used to analyze systems in uncertainty quantification. Furthermore, several approaches exist to determine a low-dimensional approximation (or sparse approximation) for some quantity of interest in a model, where just a few orthogonal basis polynomials are required. In this work, we consider linear dynamical systems consisting of ordinary differential equations with random variables. The aim of this paper is to explore methods for producing low-dimensional approximations of the quantity of interest further. We investigate two numerical techniques to compute a low-dimensional representation, which both fit the approximation to a set of samples in the time domain. On the one hand, a frequency domain analysis of a stochastic Galerkin system yields the selection of the basis polynomials. It follows a linear least squares problem. On the other hand, a sparse minimization yields the choice of the basis polynomials by information from the time domain only. An orthogonal matching pursuit produces an approximate solution of the minimization problem. Finally, we compare the two approaches using a test example from a mechanical application.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Hyperspectral Image Classification using a Self-Organizing Map

The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

Martinez, P.↗
DOE OSTI2020

Flow-based likelihoods for non-Gaussian inference

We investigate the use of data-driven likelihoods to bypass a key assumption made in many scientific analyses, which is that the true likelihood of the data is Gaussian. In particular, we suggest using the optimization targets of flow-based generative models, a class of models that can capture complex distributions by transforming a simple base distribution through layers of nonlinearities. We call these flow-based likelihoods (FBL). We analyze the accuracy and precision of the reconstructed likelihoods on mock Gaussian data, and show that simply gauging the quality of samples drawn from the trained model is not a sufficient indicator that the true likelihood has been learned. We nevertheless demonstrate that the likelihood can be reconstructed to a precision equal to that of sampling error due to a finite sample size. We then apply FBLs to mock weak lensing convergence power spectra, a cosmological observable that is significantly non-Gaussian (NG). We find that the FBL captures the NG signatures in the data extremely well, while other commonly used data-driven likelihoods, such as Gaussian mixture models and independent component analysis, fail to do so. This suggests that works that have found small posterior shifts in NG data with data-driven likelihoods such as these could be underestimating the impact of non-Gaussianity in parameter constraints. By introducing a suite of tests that can capture different levels of NG in the data, we show that the success or failure of traditional data-driven likelihoods can be tied back to the structure of the NG in the data. Here, unlike other methods, the flexibility of the FBL makes it successful at tackling different types of NG simultaneously. Because of this, and consequently their likely applicability across datasets and domains, we encourage their use for inference when sufficient mock data are available for training.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Structural and mechanistic basis for protein glutamylation by the kinase fold

The kinase domain transfers phosphate from ATP to substrates. However, the Legionella effector SidJ adopts a kinase fold, yet catalyzes calmodulin (CaM)-dependent glutamylation to inactivate the SidE ubiquitin ligases. The structural and mechanistic basis in which the kinase domain catalyzes protein glutamylation is unknown. Here, in this work, we present cryo-EM reconstructions of SidJ:CaM:SidE reaction intermediate complexes. We show that the kinase-like active site of SidJ adenylates an active-site Glu in SidE, resulting in the formation of a stable reaction intermediate complex. An insertion in the catalytic loop of the kinase domain positions the donor Glu near the acyl-adenylate for peptide bond formation. Our structural analysis led us to discover that the SidJ paralog SdjA is a glutamylase that differentially regulates the SidE ligases during Legionella infection. Our results uncover the structural and mechanistic basis in which the kinase fold catalyzes non-ribosomal amino acid ligations and reveal an unappreciated level of SidE-family regulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Disentangling the Effects of Temperature, Moisture, and Substrate Availability on Soil CO 2 Efflux

Soil respiration ($R_s$), the largest carbon emission flux in ecosystems, is usually modeled as an empirically parameterized function of temperature, and sometimes water availability. The likely contribution by other factors, such as carbohydrate substrate supply from photosynthesis, has been recognized, but modeling capacity to use this information is limited. Wavelet transformations of the residuals of a seasonal Q 10 temperature response model indicated structure at different temporal scales. In this work, we hypothesize that this indicates the lack of explicit representation of relevant processes in the models. Using cross-spectral analysis, we found that time series of photosynthetically active radiation explained most of the diurnal variation, temperature, explained variability at multiple time scales (diurnal-synoptic), whereas volumetric soil water content correlated with variability in Rs at scales 15-30 days. The results suggest that the time domains of influence for different driving variables of $R_s$ are discrete, and largely nonoverlapping, and represent functional relationships between soil biological activity and its constraints. Analysis of phase angles showed that $R_s$ lagged photosynthetically active radiation by 1.5-3.0 hr. As this time lag was the same in both young and mature trees, with more than fivefold difference in transport distances, we hypothesize that this finding adds to the body of literature that support the pressure-concentration-wave model of carbohydrate availability in plants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Laboratory Instrument Software Controlled Spread Spectrum Time Domain Reflectometry for Electrical Cable Testing

This research discusses development of a software-controlled laboratory instrument based spread spectrum time domain reflectometry system (SSTDR). This constitutes one task within PNNL’s Light Water Sustainability Program (LWRS) whose mission includes advancing nondestructive examination (NDE) techniques for off-line and on-line in-situ cable condition monitoring. In 2022, PNNL evaluated SSTDR for detection and characterization of a number of cable anomalies (Glass et al. 2022). The review included comparison of SSTDR to Frequency Domain Reflectometry (FDR) techniques which have enjoyed encouraging feedback and are starting to be used in nuclear power plants for periodic cable condition monitoring of cable systems as part of the plant’s overall cable aging management program. The FDR test introduces a broad-band chirp onto the cable at the cable end then listens for any reflection from a change of impedance along the cable caused by a damaged conductor or insulation, splices, contact with moisture, or other cable anomalies. The signal is captured in the frequency domain then transformed back to the time domain using an inverse Fourier transform (IFT). Based on the velocity of propagation, the impedance response signal is plotted against distance along the cable. Peak locations along the X-axis indicate the distance along the cable where a portion of the signal has been reflected back to the instrument as a result of a cable anomaly. The FDR test is considered the gold standard of reflectometry however it does require the cable to be de-energized to perform the test. The LIVEWIRE commercial SSTDR produces a similar plot to the FDR however all processing is in the time domain. A pseudo-random noise code (PN code) is input onto the cable conductor and the instrument listens for any reflected response from cable anomalies. The SSTDR processes the signal as an autocorrelation comparing the input PN code to any reflected signal detected. The autocorrelation analysis for thermal aging, water and water ingress detection, ground fault and phase-to-phase fault detection at various locations along the cable and with the cable attached and detached from a motor load, and on both energized and un-energized conditions were performed. These results were contrasted to Frequency Domain Reflectometry (FDR) measurements of the un-energized cable. Results were encouraging but indicated more work was warranted – particularly with the SSTDR, it seemed that the insulation damage would likely be better evaluated with multiple bandwidth cable tests particularly including larger bandwidths than were possible with the current commercial instrument. The commercial instrument’s bandwidth was set at 6, 12, 24, and 48MHz but note that SSTDR and FDR definitions of bandwidth trend similarly but are not the same. The FDR response could be more broadly adjusted, and the bandwidth of 100 to 500 MHz produced the best responses. FDR responses to anomalies were clearer than SSTDR responses and indications were that a broader bandwidth SSTDR may lead to improved SSTDR detection capability. This project used a laboratory instrument based SSTDR (primarily using an Arbitrary Waveform Generator (AWG) and a digital oscilloscope plus Python in-house software) that allowed software adjustment of the SSTDR bandwidth, window functions applied to the exciting Pseudo-random Noise (PN) code plus and other aspects of the SSTDR signal processing. Hereafter, this will be referred to as the PNNL SSTDR. Evaluating specific performance of the PNNL SSTDR is left to a separate report. This report documents hardware and software development to produce the SSTDR cable test system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Multifrequency spectrum analysis using fully digital G Mode-Kelvin probe force microscopy

Since its inception over two decades ago, Kelvin probe force microscopy (KPFM) has become the standard technique for characterizing electrostatic, electrochemical and electronic properties at the nanoscale. In this work, we present a purely digital, software-based approach to KPFM utilizing big data acquisition and analysis methods. General Mode (G-Mode) KPFM, works by capturing the entire photodetector data stream, typically at the sampling rate limit, followed by subsequent de-noising, analysis and compression of the cantilever response. We demonstrate that the G-Mode approach allows simultaneous multi-harmonic detection, combined with on-the-fly transfer function correction required for quantitative CPD mapping. The KPFM approach outlined in this work significantly simplifies the technique by avoiding cumbersome instrumentation optimization steps (i.e. lock in parameters, feedback gains etc.), while also retaining the flexibility to be implemented on any atomic force microscopy platform. We demonstrate the added advantages of G-Mode KPFM by allowing simultaneous mapping of CPD and capacitance gradient (C') channels as well as increased flexibility in data exploration across frequency, time, space, and noise domains. As a result, G-Mode KPFM is particularly suitable for characterizing voltage sensitive materials or for operation in conductive electrolytes, and will be useful for probing electrodynamics in photovoltaics, liquids and ionic conductors.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Strategic supply system design – a holistic evaluation of operational and production cost for a biorefinery supply chain

Abstract Pioneer cellulosic biorefineries across the United States rely on a conventional feedstock supply system based on one‐year contracts with local growers, who harvest, locally store, and deliver feedstock in low‐density format to the conversion facility. While the conventional system is designed for high biomass yield areas, pilot scale operations have experienced feedstock supply shortages and price volatilities due to reduced harvests and competition from other industries. Regional supply dependency and the inability to actively manage feedstock stability and quality, provide operational risks to the biorefinery, which translate into higher investment risk. The advanced feedstock supply system based on a network of depots can mitigate many of these risks and enable wider supply system benefits. This paper compares the two concepts from a system‐level perspective beyond mere logistic costs. It shows that while processing operations at the depot increase feedstock supply costs initially, they enable wider system benefits including supply risk reduction (leading to lower interest rates on loans), industry scale‐up, conversion yield improvements, and reduced handling equipment and storage costs at the biorefinery. When translating these benefits into cost reductions per liter of gasoline equivalent ( LGE ), we find that total cost reductions between –$0.46 to –$0.21 per LGE for biochemical and –$0.32 to –$0.12 per LGE for thermochemical conversion pathways are possible. Naturally, these system level benefits will differ between individual actors along the feedstock supply chain. Further research is required with respect to depot sizing, location, and ownership structures. Published 2015. This article is a U.S. Government work and is in the public domain in the USA. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗
DOE OSTI2015

Uncertainty quantification of calculated temperatures for advanced gas reactor fuel irradiation experiments

This paper presents the quantification of uncertainty of the calculated temperature data for the Advanced Gas Reactor (AGR) fuel irradiation experiments conducted in the Advanced Test Reactor at Idaho National Laboratory in support of the Advanced Reactor Technology Research and Development program. Recognizing uncertainties inherent in physics and thermal simulations of the AGR tests, the results of the numerical simulations are used in combination with statistical analysis methods to improve qualification of measured data. The temperature simulation data for AGR tests are also used for validation of the fission product transport and fuel performance simulation models. These crucial roles of the calculated fuel temperatures in ensuring achievement of the AGR experimental program objectives require accurate determination of the model temperature uncertainties. To quantify the uncertainty of AGR calculated temperatures, this study identifies and analyzes ABAQUS model parameters of potential importance to the AGR predicted fuel temperatures. The selection of input parameters for uncertainty quantification of the AGR calculated temperatures is based on the ranking of their influences on variation of temperature predictions. Thus, selected input parameters include those with high sensitivity and those with large uncertainty. Propagation of model parameter uncertainty and sensitivity is then used to quantify the overall uncertainty of AGR calculated temperatures. Expert judgment is used as the basis to specify the uncertainty range for selected input parameters. The input uncertainties are dynamic accounting for the effect of unplanned events and changes in thermal properties of capsule components over extended exposure to high temperature and fast neutron irradiation. The sensitivity analysis performed in this work went beyond the traditional local sensitivity. Using experimental design, analysis of pairwise interactions of model parameters was performed to establish sufficiency of the first-order (linear) expansion terms in constructing the response surface. To achieve completeness, uncertainty propagation made use of pairwise noise correlations of model parameters. Furthermore, time-dependent sensitivity over the test campaign duration was obtained using an interpolation scheme over the input parameter domain. This allows computation of uncertainty for the predicted peak fuel temperatures and the predicted graphite temperatures at TC locations over the whole AGR irradiation period.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Comparative Performance of Low Global Warming Potential (GWP) Refrigerants as Replacement for R-410A in a Regular 2-Speed Heat Pump for Sustainable Cooling

Heat pumps are currently being developed to reduce the energy footprint for residential and commercial building space conditioning and water heating loads in cold climates. To mitigate the nocuous impact of greenhouse gas emissions on the environment, and to create a carbon-neutral building stock, alternate lower-GWP refrigerants must also replace the predominant use of R-410A, without re-engineering the mechanical hardware. In this paper, we analyze the performance of lower-GWP alternative refrigerants (R-32, R-452B, R-454B, and R-466A) relative to the conventional R-410A and draw conclusions on the relative performances to meet cooling loads. The simulations are accomplished using the heat pump design model, a well-known, public-domain design tool with a free web interface and downloadable desktop version to support public use and the HVAC R&D community. The contributions contain detailed, hardware-based heat exchanger and system analyses to provide a comprehensive assessment. The results of the simulation are scrutinized from the first (capacity and energy efficiency) and second laws (exergy analysis) to identify sources of systemic inefficiency, the root cause of lost work. This rigorous approach provides an exhaustive analysis of alternate lower-GWP refrigerants to replace R-410A using the same hardware. The results have practical value in engineering heat pumps in an economy that is compelled to alter by the consequences and uncertainties of climate change, to reduce its anthropogenic carbon footprint.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗