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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

A Mixed Real and Floating-Point Solver

Reasoning about mixed real and floating-point constraints is essential for developing accurate analysis tools for floating-point pro- grams. This paper presents FPRoCK, a prototype tool for solving mixed real and floating-point formulas. FPRoCK transforms a mixed formula into an equisatisfiable one over the reals. This formula is then solved using an off-the-shelf SMT solver. FPRoCK is also integrated with the PRECiSA static analyzer, which computes a sound estimation of the round-off error of a floating-point program. It is used to detect infeasible computational paths, thereby improving the accuracy of PRECiSA.

Salvia, Rocco↗
NASA NTRS2020

Multi-Point Line Focused Laser Differential Interferometer for High-Speed Flow Fluctuation Measurements

A multi-point focused laser differential interferometer (FLDI) has been developed to measure density fluctuations at 16 points along a line. A pair of cylindrical lenses on the transmitter side of a conventional single-point FLDI instrument form two closely spaced (≤200 μm), orthogonally polarized, parallel laser lines at the instrument’s focus. On the receiver side of the instrument, the interference of the beams on a 16-element photodiode array results in a single line of measurements. The further addition of a Nomarski prism creates two separate measurement lines, and the addition of a second photodiode array to the instrument enables simultaneous measurements of density fluctuations along the two lines separated by several millimeters. These two lines of measurement can be conveniently oriented at any azimuthal angle relative to the instrument’s optical axis on the measurement plane, coinciding with the instrument’s focus. Two experiments were performed to demonstrate the capabilities of the instrument. In the first experiment, a laser-induced breakdown spark generated a traveling spherical shock wave, and measurements of the resulting density disturbance and wave velocity were obtained. These results were compared to high-speed schlieren images of the shock wave acquired at 400 kHz. In the second experiment, the multi-point FLDI instrument was used to measure density disturbances in the boundary layer of a flat plate in a Mach 6 freestream flow. The measurements were made along two lines, both approximately 6 mm in length, extending from the surface of the plate through the boundary layer. High-speed schlieren images were acquired at 100 kHz during separate wind tunnel runs at matching unit Reynolds numbers to visualize the unsteady boundary layer flow and compare to the FLDI measurements.

Laser beam shaping↗
NASA NTRS2021

ICESat-2 Pointing Calibration and Geolocation Performance

ICESat-2 science requirements are dependent on the accurate real-time pointing control (i.e. geolocation control) and post-processed geolocation knowledge of the laser altimeter surface returns. Pre-launch pointing alignment errors and post-launch pointing alignment variation result in large geolocation errors that must be calibrated on orbit. In addition, the changing sun-orbit geometry causes thermal-mechanical forced laser frame alignment variations at the orbit period and trends from days, weeks and months. Early mission analysis computed precise post-launch laser beam alignment calibration. The alignment calibration was uploaded to the spacecraft and enabled the pointing control performance to achieve 4.4 ± 6.0 m, a significant improvement over the 45 m (1 σ) mission requirement. Laser frame alignment calibrations are used to reduce the alignment bias and time variation, as well as the orbital variation contributions to geolocation knowledge error from 6 m to 1.7 m (1 σ). Relative beam alignment of the six beams is calibrated and shown to contribute between 0.5 ± 0.1 m and 2.4 ± 0.2 m of remaining geolocation knowledge error. Independent geolocation assessment based on comparison to high-resolution digital elevation models agrees well with the calibration geolocation error estimates. The analysis demonstrates the ICESat-2 mission is performing far better than its geolocation knowledge requirement of 6.5 m (1 σ) after the laser frame alignment bias variation and orbital variation calibrations have been applied. Remaining geolocation error is beam dependent and ranges from 2.5 m for beam 6 to 4.4 m for beam 2 (mean + 1 σ).

S. B. Luthcke↗
NASA NTRSDate not supplied

Pointing, Acquisition, and Tracking for the TBIRD Cubesat Mission: System Design and Pre-Flight Results

The Terabyte InfraRed Delivery (TBIRD) program will establish a communication link from a nanosatellite in low-Earth orbit to a ground station at burst rates up to 200 Gbps. The TBIRD payload is currently in the process of integrating with the 6-U CubeSat host bus and pre-flight testing has been completed. An overview of the pointing, acquisition, and tracking system for TBIRD is provided as well as a summary of results from pre-flight testing. TBIRD relies on the spacecraft bus to implement fine pointing corrections supplied by its quad sensor at a rate of 10 Hz. The measured accuracy of pointing feedback is about 10μrad RMS per axis. A custom optical assembly was designed for transmitter/receiver alignment stability which was measured to be within 25μrad two-axis through environmental testing. With TBIRD feedback in the loop, single axis pointing accuracy of the downlink is predicted to be about 30μrad RMS.

space communications↗
NASA NTRS2021

ICESat-2 Pointing Calibration and Geolocation Performance

ICESat-2 science requirements are dependent on the accurate real-time pointing control (i.e., geolocation control) and postprocessed geolocation knowledge of the laser altimeter surface returns. Prelaunch pointing alignment errors and postlaunch pointing alignment variation result in large geolocation errors that must be calibrated on orbit. In addition, the changing sun-orbit geometry causes thermal-mechanical forced laser frame alignment variations at the orbit period and trends from days, weeks, and months. Early mission analysis computed precise postlaunch laser beam alignment calibration. The alignment calibration was uploaded to the spacecraft and enabled the pointing control performance to achieve 4.4 ± 6.0 m, a significant improvement over the 45 m (1 σ) mission requirement. Laser frame alignment calibrations are used to reduce the alignment bias and time variation, as well as the orbital variation contributions to geolocation knowledge error from 6 to 1.7 m (1 σ). Relative beam alignment of the six beams is calibrated and shown to contribute between 0.5 ± 0.1 m and 2.4 ± 0.2 m of remaining geolocation knowledge error. Independent geolocation assessment based on comparison to high-resolution digital elevation models agrees well with the calibration geolocation error estimates. The analysis demonstrates the ICESat-2 mission is performing far better than its geolocation knowledge requirement of 6.5 m (1 σ) after the laser frame alignment bias variation and orbital variation calibrations have been applied. Remaining geolocation error is beam dependent and ranges from 2.5 m for beam 6 to 4.4 m for beam 2 (mean + 1 σ).

S B Luthcke↗
NASA NTRS2022

Vegetation and vantage point influence visibility across diverse ecosystems: Implications for animal ecology

Visual information can influence animal behavior and habitat use in diverse ways. Visibility is the property that relates 3D habitat structure to accessibility of visual information. Despite the importance of visibility in animal ecology, this property remains largely unstudied. Our objective was to assess how habitat structure from diverse environments and animal position within that structure can influence visibility. We gathered terrestrial lidar data (1 cm at 10 m) in four ecosystems (forest, shrub-steppe, prairie, and desert) to characterize viewsheds (i.e., estimates of visibility based on spatially explicit sightlines) from multiple vantage points. Both ecosystem-specific structure and animal position influenced potential viewsheds. Generally, as height of the vantage point above the ground increased, viewshed extent also increased, but the relationships were not linear. In low-structure ecosystems (prairie, shrub-steppe, and desert), variability in viewsheds decreased as vantage points increased to heights above the vegetation canopy. In the forest, however, variation in viewsheds was highest at intermediate heights, and markedly lower at the lowest and highest vantage points. These patterns are likely linked to the amount, heterogeneity, and distribution of vegetation structure occluding sightlines. Our work is the first to apply a new method that can be used to estimate viewshed properties relevant to animals (i.e., viewshed extent and variability). We demonstrate that these properties differ across terrestrial landscapes in complex ways that likely influence many facets of animal ecology and behavior.

Rachel Stein↗
DOE OSTI2022

“Tailing” Phenomenon During Polymer Propagation at The Milne Point Polymer Flood

Chemical flooding simulators traditionally assume that polymer retention follows the Langmuir isotherm, while fractional-flow calculations assume concentration-independent retention. Both models predict a delay in propagation of the polymer front (in proportion to the retention value), followed by a rapid rise in produced polymer concentration to the injected level. In contrast, laboratory retention studies for the Milne Point polymer flood (North Slope of Alaska) consistently show virtually no delay in polymer propagation, a rapid rise in produced polymer to 70-90% of the injected concentration, followed by produced concentration gradually approaching the injected value over many pore volumes. From a practical viewpoint, this behavior means that retention causes no significant delay in propagation of the polymer bank (and therefore the oil bank), but the effective viscosity and displacement efficiency are less than originally planned. This paper explores why this polymer “tailing” phenomenon occurs. During core floods, effluent was analyzed for brine-tracer concentration, viscosity, total organic carbon, and total nitrogen. The latter three items allowed three independent measures of polymer concentration and polymer retention. Experiments were performed with Milne Point core material, oil, brine, and conditions. Mechanistic experiments were also performed with packs of glass beads with controlled levels of various minerals. In Milne Point cores, the presence of the tailing phenomenon was not sensitive to flow rate, polymer concentration, core heterogeneity, or whether the core was preserved, cleaned of oil, or cleaned and resaturated with oil, or cleaned, re-saturated and aged with oil. The three independent measures of polymer concentration confirmed that the tailing phenomenon was not an artifact associated with polymer degradation or detection interferences. Tailing was also observed during mechanistic floods using glassbead packs when sufficient levels of illite or kaolinite were present. This observation was consistent with high levels of illite noted in Milne Point cores. The tailing was not noted during mechanistic floods that contained beads with montmorillonite, chlorite, calcium carbonate, dolomite, siderite, pyrite, or calcium sulfate. A model is proposed to account for the tailing phenomenon. This work suggests that mineralogy analysis (especially for illite and kaolinite) may reveal whether tailing should be accounted for during simulations of polymer propagation/retention in a given field application.

Seright, Randy↗
DOE OSTI2022

NEAR CRITICAL POINT TESTING AND PERFORMANCE RESULTS OF A SCO2 COMPRESSOR FOR A 10MWE BRAYTON CYCLE

Development and commercial acceptance of sCO2 Brayton cycles for power generation applications are growing rapidly as they offer performance advantages over other cycles. To maximize the cycle performance, the compressors are designed to operate near the critical point of the working fluid. At the critical point the fluid properties change rapidly with variations in inlet conditions. This makes it challenging to both accurately predict the performance and guarantee the operability of the compressor, as the behavior is affected by these slight variations in inlet conditions. A full scale 1st stage main compressor for a 10MWe-Class recompression Brayton cycle was built and tested to validate performance and operability in this unique operating range. The compressor was tested in a laboratory environment with additional instrumentation, beyond what is required by PTC-10, to minimize the uncertainty in the measured performance. Complete constant speed characteristics were collected at multiple supercritical points, operating at constant inlet conditions for each speed line covering a range of compressor inlet densities from 400 to 600 kg/m3. Variations in the compressor stage efficiency and choke margin were observed, and the overall operability and stability of the compressor in response to changes in operating condition were also monitored. The compressor was shown to have excellent performance that closely matched the original design prediction. The performance at various inlet conditions showed minimal change in isentropic head coefficient at the design flow, but did show some variation in efficiency and choke margin across the map. These changes in performance were observed to be minimal, and did not affect the stable operation of the compressor. The results demonstrate that a commercial scale sCO2 compressor can operate near the critical point and achieve the high levels of performance and stability required for power generation applications.

pelton, rob↗
DOE OSTI2024

Economic and Jobs Impacts of Point-Source Carbon Capture in Cement Industry – Case Study

The cement industry accounts for an estimated 8% of global CO2 emissions, which surpasses that of the entire aviation sector. In contrast with other industries, where CO2 emissions can be drastically reduced via electrification or fuels substitution, cement production releases CO2 as part of its process, during the calcination of carbonates to yield oxides. Thus, point-source carbon capture has become a key technology in the cement industry’s decarbonization. Apart from the expected environmental benefits, point-source carbon capture in the cement industry can yield important economic benefits and create jobs. The objective of this study was to perform a preliminary assessment of the economic and workforce impacts associated with the construction and operation of a point-source carbon capture retrofit of an existing cement production facility, using as a basis the data from a front-end engineering design (FEED) study to install a 3.9 million metric tons per year (Mtpy) CO2 capture facility at Holcim Ste Genevieve cement plant in Missouri, United States of America. The advanced carbon capture technology used in this FEED study was Air Liquide’s Cryocap™ FG carbon capture technology. The study evaluated the direct, indirect, and induced economic impacts of the construction, operation, and maintenance activities of the project over its lifespan. It also covered how the project will generate new jobs, their nature, and quantity, along with strategies to prepare the workforce. To perform this study, construction, operation, and maintenance cost estimates, as well as construction and operation staffing plans from the FEED study were input into IMPLAN version 7.5 software, licensed by IMPLAN Group LLC (Huntersville, VC), to predict the direct, indirect and induced economic impacts of the project using industry multipliers from the software. Additionally, recruitment strategies were developed for hiring individuals who belong to groups that are historically underserved or underrepresented, as well as anticipated recruitment of workers from the local community (whether training will be required or if the skills are associated with an existing labor force). The analysis estimated that the construction and operation of the carbon capture at Holcim Ste. Genevive will result in over 24 thousand work-years of job opportunities, close to USD 10 billion of economic impacts, including over USD 460 million of tax revenue. These results encompass the direct, indirect, and induced effects. A strategy to maximize hiring from the project and neighboring counties was developed, leveraging training agreements with local trade groups and universities. The result of this study can be used for a strategic preliminary assessment of the potential regional economic and job impacts of retrofitting existing cement plants with point source carbon systems, and its methodology can be replicated to individual projects to aid in planning and workforce development.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

A Scalable Interior‐Point Gauss–Newton Method for PDE‐Constrained Optimization With Bound Constraints

Here, we present a scalable approach to solve a class of partial differential equation (PDE)‐constrained optimization problems with bound constraints. This approach utilizes a robust full‐space interior‐point (IP)‐Gauss–Newton optimization method. To cope with the poorly‐conditioned IP‐Gauss–Newton saddle‐point linear systems that need to be solved approximately, once per optimization step, we propose two spectrally related preconditioners. These preconditioners leverage the limited informativeness of data in regularized PDE‐constrained optimization problems. A block Gauss–Seidel preconditioner is proposed for the GMRES‐based solution of the IP‐Gauss–Newton linear systems. It is shown, for a large‐class of PDE‐ and bound‐constrained optimization problems, that the spectrum of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix is asymptotically independent of discretization and is not impacted by the ill‐conditioning that notoriously plagues interior‐point methods. We exploit symmetry of the IP‐Gauss–Newton linear systems and propose a regularization and log‐barrier Hessian preconditioner for the preconditioned conjugate gradient (PCG)‐based solution of the equivalent IP‐Gauss–Newton–Schur complement linear systems. The eigenvalues of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix, that are not equal to one, are identical to the eigenvalues of the regularization and log‐barrier Hessian preconditioned Schur complement matrix. The scalability of the approach is demonstrated on two example problems. The numerical solution of these optimization problems is shown to require a discretization independent number of IP‐Gauss–Newton linear solves. Furthermore, the linear systems are solved in a discretization and IP ill‐conditioning independent number of preconditioned Krylov subspace iterations. The parallel scalability of the preconditioner, achieved via algebraic multigrid component solvers when applicable, and the aforementioned algorithmic scalability permits a parallel scalable means to compute solutions of a large class of PDE‐ and bound‐constrained problems.

PDE-constrained optimization↗
DOE OSTI2025

Toward engineering lattice structures with the material point method (MPM)

This study examines the potential of two variants of the material point method—the generalized interpolation material point (GIMP) and dual domain material point (DDMP) methods—in developing a robust computational framework for engineering lattice structures under different loading conditions. The study begins with assessing the ability of the two methods in predicting elastic buckling phenomena using column geometries with and without initial geometric imperfections. The results indicate that both methods effectively capture buckling phenomena when initial geometric imperfections are introduced. After this verification step, we create several models of tetrahedral lattice structures with varying strut diameter and orientation and subject them to quasi-static loading. We then validate the numerical results using laboratory test results. The results show that, while both methods accurately predict load–displacement curves in the pre-buckling regime, their predictive capabilities diminish in the post-buckling regime. Through visual comparison between the numerical and experimental deformed shapes, it appears that the discrepancies between model and experimental results are attributed to initial geometric imperfections in the lattices that occurred during 3D printing. We then establish a second set of lattice models where different types of initial geometric imperfections are considered. The results from these models show that imperfections have a negligible influence in the pre-buckling regime but affect the behavior considerably in the post-buckling regime. As a final step in this work, we subject the lattice models to impact loading and employ hypothetical soft and stiff materials. These results show that the lattice stiffness, which depends on material stiffness, strut diameter, and orientation, significantly influences the ability of a lattice structure to resist impact. In particular, we find that a stiffer lattice (i.e., one made with a stiff material and thicker struts) is capable of absorbing more energy than a softer one during impact. Although material nonlinearities, inelasticity, and detailed contact formulations are not considered in this study, the findings obtained herein lay the groundwork for engineering lattice structures under extreme loading conditions through a simulation-driven framework based on particle-based methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

An infeasible-start framework for convex quadratic optimization, with application to constraint-reduced interior-point and other methods

A framework is proposed for solving general convex quadratic programs (CQPs) from an infeasible starting point by invoking an existing feasible-start algorithm tailored for inequality-constrained CQPs. The central tool is an exact penalty function scheme equipped with a penalty-parameter updating rule. The feasible-start algorithm merely has to satisfy certain general requirements, and so is the updating rule. Under mild assumptions, the framework is proved to converge on CQPs with both inequality and equality constraints and, at a negligible additional cost per iteration, produces an infeasibility certificate, together with a feasible point for an (approximately) ℓ 1 -least relaxed feasible problem, when the given problem does not have a feasible solution. The framework is applied to a feasible-start constraint-reduced interior-point algorithm previously proved to be highly performant on problems with many more inequality constraints than variables (“imbalanced”). Numerical comparison with popular codes (OSQP, qpOASES, MOSEK) is reported on both randomly generated problems and support-vector machine classifier training problems. The results show that the former typically outperforms the latter on imbalanced problems. Finally, application of the proposed infeasible-start framework to other feasible-start algorithms is briefly considered, and is tested on a simplex iteration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Bubble Point Measurements of cis-1,1,1,4,4,4-Hexafluorobutene [R-1336mzz(Z)] + trans-1,2-Dichloroethene [R-1130(E)] mixtures

Saturation pressures of pure R-1336mzz(Z) and R-1130(E) and bubble point pressures of three R-1336mzz(Z)/1130(E) blends were measured from 265 K to 360 K. For each pure refrigerant or refrigerant blend, a total of twenty unique saturation pressures or bubble points were measured. In total 100 unique state points were obtained. Presently, no Helmholtz-energy-explicit type equation of state (EoS) is available for R-1130(E). While an extended corresponding states EoS for R-1130(E) is available to estimate the properties of the R-1336mzz(Z)/1130(E) blend, this model does not resolve the azeotropic behavior of the mixture. Therefore, the perturbed-chain statistical-associating fluid theory (PC-SAFT) EoS is used to model the vapor–liquid equilibria of the R-1336mzz(Z)/1130(E) blend. PC-SAFT model parameters are reported, and the overall performance of the model is characterized by deviations from the experimental data.

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

Atomistically-informed modeling of point defect clustering and evolution in irradiated ThO 2

A cluster dynamics (CD) model has been developed to investigate the nucleation and growth of point defect clusters, i.e., interstitial prismatic loops and nanoscale and sub-nanoscale voids, in ThO 2 during irradiation by energetic particles. The model considers cluster off-stoichiometry due to the asymmetry of point defect generation on the O and Th sublattices under irradiation, as well as the point defect diffusivities and the defect binding energies to clusters. The energies were established using detailed molecular dynamics simulations considering the statistical variability of cluster configuration. A high-order adaptive time-integration has been used to solve the model. The predicted loop density and their average size is in good agreement with reported experimental observations for proton irradiated ThO 2 at 600°C. In conclusion, the model did not predict void evolution due to the sluggish kinetics of cation vacancies, explaining the absence of voids in proton irradiated ThO 2 (and other oxides) at relatively low temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Saddle point search with dynamic active volume

Sampling potential energy surface (PES) is critical for many problems in materials science, chemistry, physics, and biology and requires highly efficient saddle point searches (SPS). In the study, we introduce the concept of dynamic active volume (DAV) in addition to the active volume in self-evolving atomistic kinetic Monte Carlo (SEAKMC). The DAV method has further reduced the dimensionality of the PES at the elevation stage of a SPS. At the subsequent converging stage, the dynamic boundary in DAV is lifted to allow the system to converge to the right location of a saddle point. Coupled with the dimer method, the DAV method not only significantly reduces the time cost for a given search attempt, but also dramatically increases the probability of finding relevant saddle points for PES sampling. Further, a Python software package within the framework SEAKMC (SEAKMC_py) with the DAV method has been developed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Revisiting point defect thermodynamics in group IVB and VB transition metal carbides

We present a comprehensive re-examination of point defect thermodynamics in group IVB and VB transition metal carbides (TMCs) with the rocksalt structure using a combination of density functional theory (DFT) calculations and a statistical mechanical Wagner-Schottky model within the canonical ensemble. The most stable configurations of point defects were discovered using basin-hopping global optimization, driven by either a machine learning interatomic potential (MLIP) or DFT. A key finding is the identification of previously unreported dicarbon antisites—a C–C dimer occupying a metal site—as the structural (constitutional) defects on the carbon-rich side of stoichiometry in all group IVB and VB TMCs except TaC. Furthermore, dicarbon antisite-containing thermal defect complexes, such as quadruple and interbranch defects, can dominate in TMCs under specific stoichiometric and temperature conditions. In conclusion, by incorporating dicarbon antisites into the defect landscape, this work provides a revised understanding of the thermodynamics of point defects in TMCs.

Carbides↗
DOE OSTI2024

PlantSegNet: 3D point cloud instance segmentation of nearby plant organs with identical semantics

In this study, we introduce PlantSegNet, a novel neural network model for instance segmentation of nearby objects with similar geometric structures. Our work addresses the challenges of instance segmentation of plant point clouds, including the difficulty of annotating and labeling point clouds, the loss of local structural information in neural network components, and the generation of large numbers of incorrect small clusters due to poor choices of the loss function. One of the key contributions of our approach is a digital twin of sorghum, i.e., a procedural sorghum model, which was used to generate point clouds of sorghum fields. This allowed us to create a large-scale, annotated, synthetic dataset of sorghum plants that we used to train our PlantSegNet model. We demonstrated the effectiveness of our method in segmenting instances of sorghum leaves grown in outdoor field settings. To the best of our knowledge, this is the first study to address this specific instance segmentation problem for plants grown in such a setting. We compared our proposed method with other state-of-the-art methods for indoor settings, including SGPN and TreePartNet, on both synthetic and real data. Furthermore, our results show that PlantSegNet outperforms these methods regarding accuracy, robustness, and efficiency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

High salinity seawater boiling point elevation: Experimental verification

Boiling point elevation (BPE) for high salinity solutions is a crucial parameter that significantly affects the overall thermal efficiency of desalination, water treatment, and many other industrial processing systems, especially when minimum or zero liquid discharge is a key requirement. This paper addresses the discrepancies among the empirical correlations reported in the literature that were commonly used to determine BPE for seawater solutions. An evaluation of the experimental data with low solution concentration reveals that the data cannot be extrapolated to determine the BPE at high concentration (X > 140 ppt or g/kg). Besides, disparities are established within different equations used to determine the BPE for high salinity seawater. As a result of the minimal availability of experimental data of BPE for X > 140 ppt and the need to eliminate the discrepancies, an experimental setup was built, which can produce reliable and repeatable BPE data for any solution concentration. Boiling points were obtained experimentally for seawater solutions with a wide range of salinity (X between 20 and 280 ppt) and brine solution temperature (t b between 20 and 80°C). The experimental results of boiling point elevations for seawater are further compared with the experimental data and analytical results reported in the literature. The newly obtained experimental results show that the minimum and maximum BPE values for the brine solutions tested are 0.175°C at t b = 80°C and X = 20 ppt, and 11.6°C at t b = 80°C and X = 280 ppt, respectively. Furthermore, the measured BPE data for seawater concentration over 80 ppt are fitted and presented using an appropriate fitting model. The new correlation can accurately predict the BPE for high salinity seawater brines and thus should be very helpful in the design of high-energy-efficient evaporation systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗