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At least 1,585 records · Page 88

Evaluation of IMERG Satellite Precipitation Over the Land-Coast-Ocean Continuum – Part Ii: Quantification

To understand and manage water systems under a changing climate and meet an increasing demand for water, a quantitative understanding of precipitation is most important in coastal regions. The capabilities of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) V06B product for precipitation quantification are examined over three coastal regions of the United States: the West Coast, the Gulf of Mexico, and the East Coast, all of which are characterized by different topographies and precipitation climatologies. A novel uncertainty analysis of IMERG is proposed that considers environmental and physical parameters such as elevation and distance to the coastline. The IMERG performance is traced back to its components, i.e., passive microwave (PMW), infrared (IR), and morphing-based estimates. The analysis is performed using high-resolution, high-quality Ground Validation Multi-Radar/Multi-Sensor (GV-MRMS) rainfall estimates as ground reference at the native resolution of IMERG of 30 min and 0.1°. IMERG Final (IM-F) quantification performance heavily depends on the respective contribution of PMW, IR, and morph components. IM-F and its components overestimate the contribution of light rainfall (<1 mm h−1) and underestimate the contribution of high rainfall rates (>10 mm h−1) to the total rainfall volume. Strong regional dependencies are highlighted, especially over the West Coast, where the proximity of complex terrain to the coastline challenges precipitation estimates. Other major drivers are the distance from the coastline, elevation, and precipitation types, especially over the land and coast surface types, that highlight the impact of precipitation regimes.

Atmosphere↗

A Heterogeneous System for Eagle Detection, Deterrent, and Wildlife Collision Detection for Wind Turbines (Final Technical Report)

This report summarizes the design, implementation, and test of an integrated system for automated detection and deterrence of eagles, with included wind turbine blade strike detection and imaging functionality. A machine learning approach was used in conjunction with a 360° camera system for automated detection and classification of golden eagles. This was developed using footage obtained from trained golden eagles and other raptors, in collaboration with wildlife biologists and professional bird handlers. Oregon State University developed a visual deterrent system, which uses inflatable anthropomorphic sculptures with random, kinetic motion to deter eagles, and conducted limited field testing on live eagles; the deterrent can be triggered by the visual detection of eagles using the vision system. Finally, a multi-sensor module was developed that is mounted at the turbine blade root. This module measures vibration and other motions to detect blade strikes, and an integrated on-blade camera captures an image of any impacting objects. Long-term, this blade strike detection system is intended to support an automatic monitoring and certification system for the eagle detection and deterent system. Independent field testing of each system component is described. Testing of the integrated system on an operational wind turbine was conducted across three separate field tests. This includes multi-day fields tests on a General Electric 1.5MW wind turbine at the National Renewable Energy Laboratory (NREL) National Wind Technology Center (NWTC) in Boulder, CO in October 2018 and July 2019; installation procedures, test procedures, and a summary of collected data are presented. A third multi-day on-turbine field test is also presented, which was performed using a General Electric 1.5MW wind turbine at the North American Wind Research and Training Center (NAWRTC) at Mesalands Community College, Tucumcari, NM in April 2019. Across these field tests, the vision system was demonstrated using unmanned aerial vehicles (UAV), and the eagle classification algorithm was not tested; the visual deterrent system was demonstrated, including automatic, remote deployment following surrogate visual detections; and, multi-sensor on-blade data was recorded across multiple wind turbine operational conditions and through more than 100 surrogate blade strikes using soft projectiles, including the successful demonstration of automatic image capture of striking objects. This data set was also used for offline development and validation of enhanced collision detection algorithms. As summarized in this report, the development and field validation of an integrated detection, deterrent, and blade collision detection system represents a critical proof of concept for future technology development of related detection and deterrent technologies, where both deterrent as well as collision detection recording devices are needed for future siting, monitoring, and operation of wind turbine installations, both onshore and offshore.

17 WIND ENERGY↗

Melt Processed Crystalline Ceramic Waste Forms for Advanced Nuclear Fuel Cycles: CRP T21027 1813: Processing technologies for high level waste, formulation of matrices and characterization of waste forms, Task 17208 (Final Report)

A multi-phase ceramic waste form is being developed at the Savannah River National Laboratory (SRNL) for treatment of secondary waste streams generated by reprocessing commercial spent nuclear. The envisioned waste stream contains a mixture of transition, alkali, alkaline earth, and lanthanide metals. Ceramic waste forms are tailored (engineered) to incorporate waste components as part of their crystal structure based on knowledge from naturally found minerals containing radioactive and non-radioactive species similar to the radionuclides of concern in wastes from fuel reprocessing. The ability to tailor ceramics to mimic naturally occurring crystals substantiates the long term stability of such crystals (ceramics) over geologic timescales of interest for nuclear waste immobilization [1]. A durable multi-phase ceramic waste form tailored to incorporate all the waste components has the potential to broaden the available disposal options and thus minimize the storage and disposal costs associated with aqueous reprocessing. This report summarizes results from three years of work on the IAEA Coordinated Research Project on “Processing technologies for high level waste, formulation of matrices and characterization of waste forms” (T21027), and specific task “Melt Processed Crystalline Ceramic Waste Forms for Advanced Nuclear Fuel Cycles” (17208).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Axom

Axom is an open-source library of "building block" software components that provide core infrastructure capabilities for HPC applications. Such capabilities include: input file parsing and verification for various file formats, format specification for material shape input to multi-material simulations and tools for placing those shapes on meshes, parallel distributed coordination of diagnostic messages, geometric primitives, spatial queries and spatial search acceleration data structures, in memory key-value data store for managing simulation data and parallel file I/O. Axom components are used widely across LLNL Advanced Simulation and Computing program applications. It is also part of the LLNL institutionally-supported RADIUSS project, which promotes and funds its adoption by projects across LLNL.

Zagaris, George↗

Component based dataflow processing framework

In this paper we present SOA based CLAs12 event Reconstruction and Analyses (CLARA) framework used to develop Earth Science multi-sensor data fusion, processing, and analytics applications (NAIADS: NASA JLAB collaboration). CLARA design focus is on two main traits: a) real-time data stream processing, and b) service oriented architecture (SOA) in a flow based programming (FBP) paradigm. Data driven and data centric architecture of CLARA presents an environment for developing agile, elastic, multilingual data processing applications. The CLARA framework presents solutions, capable of processing large volumes of data interactively and substantially faster than batch systems.

Gyurjyan, V.↗

[Multi-Scale Convergence of Cold-Land Process Representation in Land-Surface Models, Microwave Remote Sensing, and Field Observations]

The cryosphere is a major component of the hydrosphere and interacts significantly with the global climate system, the geosphere, and the biosphere. Measurement of the amount of water stored in the snow pack and forecasting the rate of melt are thus essential for managing water supply and flood control systems. Snow hydrologists are confronted with the dual problems of estimating both the quantity of water held by seasonal snow packs and time of snow melt. Monitoring these snow parameters is essential for one of the objectives of the Earth Science Enterprise-understanding of the global hydrologic cycle. Measuring spatially distributed snow properties, such as snow water equivalence (SWE) and wetness, from space is a key component for improvement of our understanding of coupled atmosphere-surface processes. Through the GWEC project, we have significantly advanced our understandings and improved modeling capabilities of the microwave signatures in response to snow and underground properties.

Shi, Jiancheng↗

Building a new multiphysics workflow in MOOSE: application to tritium migration, trapping and advection in TMAP8

Fusion devices are anticipated to produce and consume several kilograms of tritium per year. This rare fuel resource is both highly mobile and radioactive, making tracking inventories a priority for operation and safety. The fusion safety program at the Idaho National Laboratory has been developing the Tritium Migration and Analysis Program (TMAP), of which the latest version is a MOOSE-based application. TMAP8 is verified against its predecessors and possesses additional multi-dimensional tritium migration modeling capabilities. As we extend its capabilities towards both whole device (in multiple dimensions) and whole plant (with multiple components) simulations, the syntax of inputs must become compact, descriptive, compatible with quality assurance processes, and as error-proof as achievable. The new Physics system developed MOOSE can set up equations and instantiating them on plant components. The system permits the automatic definition of complex discretization with a consistency between object parameters achieved programmatically. The Physics system can currently instantiate the equations for heat conduction and Navier Stokes weakly compressible flow. In MOOSE-terms, it automates the definition of kernels, boundary conditions, and several core and helper materials and fields. As part of this effort, Physics classes were developed for tritium migration, trapping and advection within either a multi-dimensional Navier Stokes fluid dynamics simulation, or a 1D thermal hydraulics piping system. In this presentation, we will showcase the new syntax, its application to several verification and validation cases which were already studied using the classical TMAP8 syntax, and a demonstration of the new coupling capabilities for the migration of tritium into blanket coolant channels and the subsequent advection into the coolant loop.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Validation of the aerosol optical property products derived by the GRASP/Component approach from multi-angular polarimetric observations

The multi-angle polarimetric satellite observations are helpful for improving the retrievals of aerosol parameters. However, practical applications of polarization technology are still limited because of complexity of measurement and interpretation of polarimetric observations. In this study, we analyze the performance of a new component approach developed in the frame of the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm. In addition to aerosol optical properties including particle size distribution, non-sphericity and index of refraction that are commonly derived from multi-angle radiance and polarization measurements, the GRASP/Component approach also provides some information about aerosol composition. Specifically, in this approach aerosol is modeled as an internal mixture of several components with distinctly different chemical compositions and known refractive indices. The approach is intended not only to provide additional insight on aerosol composition but also to improve retrieval of basic aerosol optical properties. This study presents comprehensive validation and evaluation of Aerosol Optical Depth (AOD), Ångstrom exponent (AE), fine mode AOD (AODF), coarse mode AOD (AODC), and single scattering albedo (SSA) as retrieved by the GRASP/Component approach. The GRASP/Component products include aerosol retrievals using two different aerosol component mixing rules, i.e., Maxwell-Garnett (MG) effective medium approximation and a simple Volume- Weighted averaging (VW). The differences between the results obtained using these two assumptions are also discussed. The obtained results show that the aerosol optical property products of GRASP/Component approach have good agreement with the ground-based AERONET measurements, which is comparable to other PARASOL/ GRASP approaches. Specifically, the AOD retrieved by GRASP/Component approach show high correlation and nearly no bias both over land and ocean, as compared with AERONET. The more detailed aerosol properties such as AE, AODF, AODC and SSA also show one of the best comparisons with AERONET. These improvements can probably be attributed to the use of the additional physical constraints on spectral dependence of the complex refractive index and the reduction of total number of aerosol parameters directly retrieved in the GRASP/Component approach. In addition, the choice of mixing rules had no significant effect on optical retrievals. With the exception of SSA, the results obtained based on the MG mixing rule were found to be slightly better over those obtained using VW mixing rule, especially for bias.

Brent N Holben↗

Multi-Agent Methods for the Configuration of Random Nanocomputers

As computational devices continue to shrink, the cost of manufacturing such devices is expected to grow exponentially. One alternative to the costly, detailed design and assembly of conventional computers is to place the nano-electronic components randomly on a chip. The price for such a trivial assembly process is that the resulting chip would not be programmable by conventional means. In this work, we show that such random nanocomputers can be adaptively programmed using multi-agent methods. This is accomplished through the optimization of an associated high dimensional error function. By representing each of the independent variables as a reinforcement learning agent, we are able to achieve convergence must faster than with other methods, including simulated annealing. Standard combinational logic circuits such as adders and multipliers are implemented in a straightforward manner. In addition, we show that the intrinsic flexibility of these adaptive methods allows the random computers to be reconfigured easily, making them reusable. Recovery from faults is also demonstrated.

Lawson, John W.↗

Multi-Star Wavefront Control: Update on Technology Development for Roman Space Telescope and Habitable Worlds Observatory

A majority of Sun-like stars have at least one stellar companion that can introduce additional noise into the field of view of any high-contrast imaging instrument, limiting the achievable contrast. These include high-quality target stars such as the A and B components of Alpha Centauri, our nearest stellar neighbor. Enabling direct imaging of binary stars has the potential to increase the scientific yield for coronagraphic instruments planned on NASA's future space missions and concepts, including the Roman Space Telescope and the Astro2020 IR/O/UV flagship. Multi-Star Wavefront Control (MSWC) is a wavefront-control technique that simultaneously removes the (mutually incoherent) stellar leakage from both stellar components, enabling direct imaging of planets in many binary star systems. MSWC is an algorithmic technique and can be used with existing wavefront control systems on coronagraphic instruments (as well as starshades if a deformable mirror is available in the optical path) including planned observations on the upcoming PICTURE-D balloon flight. We report on the latest experimental and numerical results obtained with MSWC as part of the technology development effort to demonstrate compatibility with existing high-contrast imaging platforms for this technique. We first report on functional tests carried out at Subaru's SCExAO instrument operating in-air and showing the sub-Nyquist mode at 4.1e-6 contrast in monochromatic light. The Super-Nyquist regime of MSWC was recently tested in vacuum at JPL's High Contrast Imaging Testbed (HCIT) on the Decadal Survey Testbed (DST) reaching 8.6e-9 contrast in a 10% band. We also report on results for the current stage of vacuum testing at HCIT's Occulting Mask Coronagraph (OMC) testbed using a mask similar to the contributed MSWC mask on the Roman Space Telescope's coronagraph instrument which has demonstrated suppression at the 9.8e-9 contrast at Super-Nyquist separations around the 3rd diffraction order and is planned to use a novel binary source simulator.

high-contrast imaging↗

Shergottite Lead Isotope Signature in Chassigny and the Nakhlites

The nakhlites/chassignites and the shergottites represent two differing suites of basaltic martian meteorites. The shergottites have ages less than or equal to 0.6 Ga and a large range of initial Sr-/Sr-86 and epsilon (Nd-143) ratios. Conversely, the nakhlites and chassignites cluster at 1.3-1.4 Ga and have a limited range of initial Sr-87/Sr-86 and epsilon (Nd-143). More importantly, the shergottites have epsilon (W-182) less than 1, whereas the nakhlites and chassignites have epsilon (W-182) approximately 3. This latter observation precludes the extraction of both meteorite groups from a single source region. However, recent Pb isotopic analyses indicate that there may have been interaction between shergottite and nakhlite/chassignite Pb reservoirs.Pb Analyses of Chassigny: Two different studies haveinvestigated 207Pb/204Pb vs. 206Pb/204Pb in Chassigny: (i)TIMS bulk-rock analyses of successive leaches and theirresidue [3]; and (ii) SIMS analysis of individual minerals[4]. The bulk-rock analyses fall along a regression of SIMSplagioclase analyses that define an errorchron that is olderthan the Solar System (4.61±0.1 Ga); i.e., these define amixing line between Chassigny’s principal Pb isotopic components(Fig. 1). Augites and olivines in Chassingy (notshown) also fall along or near the plagioclase regression [4].This agreement indicates that the whole-rock leachateslikely measure indigenous, martian Pb, not terrestrial contamination[5]. SIMS analyses of K-spars and sulfides definea separate, sub-parallel trend having higher 207Pb/206Pbvalues ([4]; Fig. 1). The good agreement between the bulkrockanalyses and the SIMS analyses of plagioclases alsoindicates that the Pb in the K-spars and sulfides cannot be amajor component of Chassigny.The depleted reservoir sampled by Chassigny plagioclaseis not the same as the solar system initial (PAT) andrequires a multi-stage origin. Here we show a two-stagemodel (Fig. 1) with a 238U/204Pb (μ) of 0.5 for 4.5-2.4 Gaand a μ of 7 for 2.4-1.4 Ga. This is not a unique model butdoes produce a Pb composition that falls on the plagioclaseregression at 1.4 Ga, the approximate igneous age of Chassigny [1]. It should be noted that low-μ single-stage modelsare not capable of producing sufficiently radiogenic 206Pb/204Pb at 1.4 Ga.Relation to Shergottites: The Chassigny K-spars and sulfides fall along a second mixing line defined by leachesand residues of depleted and intermediate shergottites [6]. This mixing line falls above the plagioclase regression.Therefore, we also interpret the radiogenic component of this mixing line to represent indigenous martian Pb. It ispossible that the depleted and intermediate shergottites and the Chassigny plagioclases sample radiogenic Pb from thethe same source, i.e., the mixing lines may intersect at high 206Pb/204Pb.Both K-spar and sulfide are late-stage phases. At the time of their crystallization, the Chassigny system appearsto have remained open to a depleted shergottite Pb reservoir. The depleted component of the shergottite mixing linecan be generated by a single-stage evolution from PAT (4.5 to 1.4 Ga) in a reservoir having a μ ~2. A similar modelfor the most depleted shergottites is also possible: μ = 1.5 for 4.5 to 0.3 Ga.Nakhlites: Nakhlite analyses plot between the shergottite and Chassigny plagioclase regressions [3]. So again,members of the nakhlite/chassignite suite show affinities to shergottite Pb.

Jones, J. H.↗

Five Micron High Resolution MALDI Mass Spectrometry Imaging with Simple, Interchangeable, Multi-Resolution Optical System

High-spatial resolution mass spectrometry imaging (MSI) is crucial for the mapping of chemical distributions at the cellular and subcellular level. In this work, we improved our previous laser optical system for matrix-assisted laser desorption ionization (MALDI)-MSI, from ~9 μm practical laser spot size to a practical laser spot size of ~4 μm, thereby allowing for 5 μm resolution imaging without oversampling. This is accomplished through a combination of spatial filtering, beam expansion, and reduction of the final focal length. Most importantly, the new laser optics system allows for simple modification of the spot size solely through the interchanging of the beam expander component. Using 10×, 5×, and no beam expander, we could routinely change between ~4, ~7, and ~45 μm laser spot size, in less than 5 min. We applied this multi-resolution MALDI-MSI system to a single maize root tissue section with three different spatial resolutions of 5, 10, and 50 μm and compared the differences in imaging quality and signal sensitivity. We also demonstrated the difference in depth of focus between the optical systems with 10× and 5× beam expanders. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Integrating Existing Simulation Components into a Cohesive Simulation System

A tradition of leveraging the re-use of components to help manage costs has evolved in the development of complex system. This tradition continues on in the Joint Polar Satellite System (JPSS) Program with the cloning of the Suomi National Polar-orbiting Partnership (NPP) satellite for the JPSS-1 mission, including the instrument complement. One benefit of re-use on a mission is the availability of existing simulation assets from the systems that were previously built. An issue arises in the continual shift of technology over a long mission, or multi-mission, lifecycle. As the missions mature, the requirements for the observatory simulations evolve. The challenge in this environment becomes re-using the existing components in that ever-changing landscape. To meet this challenge, the system must: establish an operational architecture that minimizes impacts on the implementation of individual components, consolidate the satisfaction of new high-impact requirements into system-level infrastructure, and build in a long-term view of system adaptation that spans the full lifecycle of the simulation system. The Flight Vehicle Test Suite (FVTS) within the JPSS Program is defining and executing this approach to ensure a robust simulation capability for the JPSS multi-mission environment

McLaughlin, Brian J.↗

Biomorphic Multi-Agent Architecture for Persistent Computing

A multi-agent software/hardware architecture, inspired by the multicellular nature of living organisms, has been proposed as the basis of design of a robust, reliable, persistent computing system. Just as a multicellular organism can adapt to changing environmental conditions and can survive despite the failure of individual cells, a multi-agent computing system, as envisioned, could adapt to changing hardware, software, and environmental conditions. In particular, the computing system could continue to function (perhaps at a reduced but still reasonable level of performance) if one or more component( s) of the system were to fail. One of the defining characteristics of a multicellular organism is unity of purpose. In biology, the purpose is survival of the organism. The purpose of the proposed multi-agent architecture is to provide a persistent computing environment in harsh conditions in which repair is difficult or impossible. A multi-agent, organism-like computing system would be a single entity built from agents or cells. Each agent or cell would be a discrete hardware processing unit that would include a data processor with local memory, an internal clock, and a suite of communication equipment capable of both local line-of-sight communications and global broadcast communications. Some cells, denoted specialist cells, could contain such additional hardware as sensors and emitters. Each cell would be independent in the sense that there would be no global clock, no global (shared) memory, no pre-assigned cell identifiers, no pre-defined network topology, and no centralized brain or control structure. Like each cell in a living organism, each agent or cell of the computing system would contain a full description of the system encoded as genes, but in this case, the genes would be components of a software genome.

Lodding, Kenneth N.↗

Circadian Effects on Simple Components of Complex Task Performance

The goal of this study was to advance understanding and prediction of the impact of circadian rhythm on aspects of complex task performance during unexpected automation failures, and subsequent fault management. Participants trained on two tasks: a process control simulation, featuring automated support; and a multi-tasking platform. Participants then completed one task in a very early morning (circadian night) session, and the other during a late afternoon (circadian day) session. Small effects of time of day were seen on simple components of task performance, but impacts on more demanding components, such as those that occur following an automation failure, were muted relative to previous studies where circadian rhythm was compounded with sleep deprivation and fatigue. Circadian low participants engaged in compensatory strategies, rather than passively monitoring the automation. The findings and implications are discussed in the context of a model that includes the effects of sleep and fatigue factors.

circadian effects↗

Assurance by Design for Cyber Physical Data-Driven Systems

Currently, Cyber Physical Data-Driven Systems (CPDDS) employ machine learning for the classification, data fusion, and control of our nation’s infrastructure, such as the power grid, transportation networks (e.g., fuel distribution, air traffic control), and DoD long-duration collaborative autonomous platforms including unmanned underwater, ground, surface, space, and aerial systems. Many CPDDSs are system-of-systems that should be designed to communicate over disadvantaged networks. It is important to assure that the CPDDSs are resilient against physical and cyber threats by design. Additionally, their design should tolerate misclassification errors resulting from natural and/or adversarial distribution shifts within their data driven components. The all-domain nature of the problem of assuring the design of CPDDSs requires a multi-disciplinary perspective as outlined in this chapter.

Chikkagoudar, Satish↗

Low‐Volume Cores for Fabrication of Compact, Versatile, and Intelligent Soft Systems

Abstract This study introduces the low‐volume core (LVC) fabrication method, which enables the monolithic molding of compact, complex, versatile, and intelligent soft robotic systems. This method uses thin and flexible thermoplastic sheets to mold internal chambers in soft fluidic actuators, valves, and circuits. The LVC fabrication method creates low‐volume networks in soft actuators (LV‐net actuators) that can be made with compact and complex geometries, enabling both low actuation volume input and multi‐degree‐of‐freedom actuators. LVC fabrication can also be used for compact, completely soft, and monolithic logic components (valves with low‐volume core, also called as LV valves) to provide directional resistance as well as a switching mechanism that enables fluidic logic in soft systems. The compatibility of the fabrication methods for both soft actuators and valves facilitates the creation of compact, integrated, and versatile soft robotic systems with embodied intelligence. This study introduces two examples of such intelligent soft robotic systems that integrate both LV‐net actuators and LV valves to demonstrate capability for complex system fabrication.

Yu, Qifan↗

Integration and Optimization of a Waste Heat Driven Organic Rankine Cycle for Power Generation in Wastewater Treatment Plants

The study focuses on achieving energy self-sufficiency in Wastewater Treatment Plants by proposing a comprehensive model for integrating, sizing, and optimizing an Organic Rankine Cycle system. The Organic Rankine Cycle system is designed to utilize waste heat from the gensets at As Samra Wastewater Treatment Plant in Jordan, where it will contribute to the overall electrical energy supply of the plant. Real data from As Samra Wastewater Treatment Plant is used to model and calculate the available waste heat using TRNSYS® software. The Organic Rankine Cycle model is then developed using ASPEN PLUS® software to explore the impact of operational parameters and determine their optimal values for maximizing the plant's energy profile. An economic analysis is conducted to assess the feasibility of the proposed model, considering system components, installation, operation, and maintenance costs. To optimize the Organic Rankine Cycle system, the study employs the Multi-Output Support Vector Regression technique to capture nonlinear relationships between independent variables (fluid type, turbine inlet pressure, turbine inlet temperature, turbine outlet pressure, and mass flow rate) and dependent variables (pump power input, waste heat input, and turbine specific work). The Osprey optimization algorithm is used to address the multi-objective optimization problem, with the proposed Pareto-based Osprey Optimization Algorithm and the Multi-Objective Particle Swarm Optimization technique being employed to evaluate critical performance and economic parameters such as system thermal efficiency, net power output, and the levelized cost of electricity. The results of the optimization strategies indicate that the M-SVR model's prediction accuracy is significantly improved after parameter optimization, with the model returning high R 2 and low Mean Square Error values of 0.991 and 0.00216, respectively. The Pareto-Based Osprey Optimization Algorithm optimizer identifies the best working fluid as Isobutane/Isopentane in a ratio of 66:34, with optimal turbine inlet pressure and temperature of 15 bars and 218 °C, respectively. In conclusion, the Organic Rankine Cycle model at these optimal conditions achieves a cycle efficiency of 19.93% and an Levelized Cost of Electricity value of 0.0353 USD/kWh.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗