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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Thermal Hydraulics Safety Analyses of TRIGA Reactor Upon Fuel Reconfiguration

Safety analyses of the Training, Research, Isotope, General Atomics (TRIGA) reactor at Kansas State University(KSU) is performed using thermal hydraulic simulations based on changes to reactivity or the volumetric heat generation rate due to changes in the positioning of the enriched fuel elements in the reactor core. If the reactivity or neutronics parameters are known, then they can be used to simulate the thermal energy state of the material which is crucial to assess the safety of the nuclear fuel inside a nuclear reactor. Several thermal hydraulics models and codes have been developed in the past to assess reactor safety. RELAP (Reactor Excursion and Leak Analysis Program) is one such tool widely used throughout the world for safety analyses. Although RELAP is considered a reliable tool by regulators, vendors, and operators, it lacks the numerical fidelity provided by 3-D computational fluid dynamics (CFD) models. This work involves the critical task of assessing safety of a research reactor upon fuel reconfiguration based on models developed in RELAP and comparing them with a commercially available 3-D CFD program. The TRIGA Mark-II reactor, designed by General Atomics and located at Kansas State University, is a class of small pool type inherently safe research reactor licensed to operate at steady state power of up to 1.25 MW. It has a cylindrical core measuring 0.45 meters diametrically and 0.38 meters axially positioned in a tank measuring 1.98 meters diametrically and 6.25 meters axially. It has uranium zirconium hydride (UZrH) fuel rods housed in stainless steel cladding material arranged in five concentric rings (B,C,D,E and F rings, in that order, moving outwards from the center). TRIGA fuel is nominally 20% enriched, but the reactivity of the fuel can be changed by using burnable poisons (not used at KSU), or by varying the total weight percent of uranium in the UZrH fuel meat. The TRIGA reactor is designed to be an inherently safe reactor and is designed to be cooled by natural convection. Thus it is of paramount importance to avoid the film boiling regime; failing to do so will subject the fuel to severe conditions, possibly resulting in its failure due to fuel/clad interactions. A high DNBR ratio is a primary consideration in the reactor core design and thus any modification in the core should ensure that this criteria is always met. In order to fully utilize the capabilities of KSU TRIGA reactor facility, it should be operated at its full capacity, i.e. 1.25 MW, which requires increasing the fuel loading in some of the E- and F-ring elements from 8.5% U (nominal) to 12.0% U (nominal). Only four elements are to be switched to 12% loading, causing local power peaking in these elements. The degree of power peaking to be expected in these 12%-loaded fuel elements was calculated based on a detailed MCNP (Monte Carlo N-Particle code) model of the reactor core. Some preliminary results of the calculations are presented in this paper based on changes in peaking factors and power levels. To predict reactor thermal behavior, axial changes in the peaking factors obtained from MCNP models were used to calculate volumetric energy density functions for a single channel one dimensional RELAP model and a three dimensional COMSOL model of the TRIGA MARK-II reactor. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Unsupervised Learning for Equitable DER Control: Preprint

In the context of managing distributed energy resources (DERs) within distribution networks (DNs), this work focuses on the task of developing local controllers. We propose an unsupervised learning framework to train functions that can closely approximate optimal power flow (OPF) solutions. The primary aim is to establish specific conditions under which these learned functions can collectively guide the network towards desired configurations asymptotically, leveraging an incremental control approach. The flexibility of the proposed methodology allows to integrate fairness-driven components into the cost function associated with the OPF problem. This addition seeks to mitigate power curtailment disparities among DERs, thereby promoting equitable power injections across the network. To demonstrate the effectiveness of the proposed approach, power flow simulations are conducted using the IEEE 37-bus feeder. The findings not only showcase the guaranteed system stability but also underscore its improved overall performance.

asymptotic stability↗
DOE OSTI2025

Digital Transformation for the Existing Fleet: Where to Start?

To remain economically viable in today’s electricity marketplace, nuclear power plants are replacing old analog equipment with modern digital tools. Having information available in an electronic format allows most work processes to become more efficient by automating simple, time-consuming tasks. However, with thousands of routine work processes performed every day, it can be difficult for the plants to know where to begin. We partnered with a nuclear utility to develop a novel assessment tool that measures seven health indicators for each work process performed, providing a rapid digital status report of the plant. The assessment tool is inexpensive and user-friendly, administered remotely, and automatically customized to each employee. Data from 167 employees representing different perspectives were analyzed to identify optimal candidates for digital initiatives that yield the highest payback for increased process efficiencies. We ranked by a priority index to ensure that processes with a good combination of time savings and digital opportunity were at the top. The focus was on determining a maximum investment to ensure that the cost savings from these initiatives are positive over a specified period. We identified potential cost savings of $2.6m, $1.3m and $1.2m for our top priority processes. By using our novel assessment tool to determine the digital status of the plant’s work processes, they were provided with a starting point for target candidates that would most benefit from a digital initiative. Our analysis helps stakeholders understand the financial impact of digital initiatives and identify maximum investment amounts when seeking technical solutions.

assessment↗
DOE OSTI2017

Augmented reality system for remote operation - 200

This paper presents a new approach to applications of augmented reality techniques for performing telerobotic operations in uncertain and hazardous environments. Particular application examples include remote or partially-automated operation of robotic manipulators in nuclear waste facilities, decommissioning sites, or as a part of incident remediation. Recently advances in virtual reality (VR) and augmented reality (AR) technology presents opportunity for enhancing the performance of such remote operations. VR can provide immersive artificial environment for the operator to interact with. As an advanced concept, AR adds to it the blending or artificial contents with real world - users are able to interact with virtual contents in the real world. This work addresses key technological innovations necessary for adopting the VR/AR technologies for the remote operation of hardware robotic systems in real world tasks. To this end, this work focuses on implementation of 'virtual fixtures', which allows intuitive and precise guidance of remote operation, as well as key enhancements in 3D sensing/reconstruction technology. In addition, the implementation details of the integration of the multi-modal augmented reality system to the telerobotic control system are presented. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Neural lumped parameter differential equations with application in friction-stir processing

Lumped parameter methods aim to simplify the evolution of spatially-extended or continuous physical systems to that of a “lumped” element representative of the physical scales of the modeled system. For systems where the definition of a lumped element or its associated physics may be unknown, modeling tasks may be restricted to full-fidelity physics simulations. Here, in this work, we consider data-driven modeling tasks with limited point-wise measurements of otherwise continuous systems. We build upon the notion of the Universal Differential Equation (UDE) to construct data-driven models for reducing dynamics to that of a lumped parameter and inferring its properties. The flexibility of UDEs allow for composing various known physical priors suitable for application-specific modeling tasks, including lumped parameter methods. The motivating example for this work is the plunge and dwell stages for friction-stir welding; specifically, (i) mapping power input into the tool to a point-measurement of temperature and (ii) using this learned mapping for process control.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Exploiting Vector and Multicore Parallelsim for Recursive, Data- and Task-Parallel Programs

Modern hardware contains parallel execution resources that are well-suited for data-parallelism-vector units-and task parallelism-multicores. However, most work on parallel scheduling focuses on one type of hardware or the other. In this work, we present a scheduling framework that allows for a unified treatment of task- and data-parallelism. Our key insight is an abstraction, task blocks, that uniformly handles data-parallel iterations and task-parallel tasks, allowing them to be scheduled on vector units or executed independently as multicores. Our framework allows us to define schedulers that can dynamically select between executing task- blocks on vector units or multicores. We show that these schedulers are asymptotically optimal, and deliver the maximum amount of parallelism available in computation trees. To evaluate our schedulers, we develop program transformations that can convert mixed data- and task-parallel pro- grams into task block-based programs. Using a prototype instantiation of our scheduling framework, we show that, on an 8-core system, we can simultaneously exploit vector and multicore parallelism to achieve 14×-108× speedup over sequential baselines.

Ren, Bin↗
DOE OSTI2023

$\mathrm{RADICAL}$-Pilot and $\mathrm{PMIx}$/$\mathrm{PRRTE}$: Executing Heterogeneous Workloads at Large Scale on Partitioned $\mathrm{HPC}$ Resources

Execution of heterogeneous workflows on high-performance computing (HPC) platforms present unprecedented resource management and execution coordination challenges for runtime systems. Task heterogeneity increases the complexity of resource and execution management, limiting the scalability and efficiency of workflow execution. Re-source partitioning and distribution of tasks execution over portioned re-sources promises to address those problems but we lack an experimental evaluation of its performance at scale. Here this paper provides a performance evaluation of the Process Management Interface for Exascale (PMIx) and its reference implementation PRRTE on the leadership-class HPC plat-form Summit, when integrated into a pilot-based runtime system called RADICAL-Pilot. We partition resources across multiple PRRTE Distributed Virtual Machine (DVM) environments, responsible for launching tasks via the PMIx interface. We experimentally measure the work-load execution performance in terms of task scheduling/launching rate and distribution of DVM task placement times, DVM startup and termination overheads on the Summit leadership-class HPC platform. Integrated solution with PMIx/PRRTE enables using an abstracted, standardized set of interfaces for orchestrating the launch process, dynamic process management and monitoring capabilities. It extends scaling capabilities allowing to overcome a limitation of other launching mechanisms (e.g., JSM/LSF). Explored different DVM setup configurations provide insights on DVM performance and a layout to leverage it. Our experimental results show that heterogeneous workload of 65,500 tasks on 2048 nodes, and partitioned across 32 DVMs, runs steady with resource utilization not lower than 52%. While having less concurrently executed tasks resource utilization is able to reach up to 85%, based on results of heterogeneous workload of 8200 tasks on 256 nodes and 2 DVMs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

MFIX-DEM Phi: Performance and Capability Improvements Towards Industrial Grade Open-source DEM Framework with Integrated Uncertainty Quantification

Two major challenges hinder the effective use and adoption of multiphase computational fluid dynamics tools by the industry. The first is the need for significant computational resources, which is inversely proportional to the accuracy of solutions due to computational intensity of the algorithms. The second barrier is assessing the prediction credibility and confidence in the simulation results. In this project, a multi-tiered approach has been proposed under four broad activities to overcome these challenges while addressing all of the objectives outlined in FOA-0001238 through Phases 1 and 2 of the project. The present report consists of the results for only Phase 1, which was the funded performance period. From the start the project, all of the objectives outlined in FOA were addressed through four major activity tasks in an integrated and balanced fashion to improve adoption of MFIX suite of solvers for industrial use. The first task aimed to improve the performance of MFIX-DEM specifically targeting to acquire the peak performance on Intel Xeon and Xeon Phi based systems, which are expected to be one of the primary high-performance computing platforms both affordable and available for the industrial users in the next two to five years. However, due to a number of changes in course of the project, the scope of the performance improvements related task was significantly reduced to avoid duplicate work. Hence, more emphasis was placed on the other three tasks as discussed below. The second task aimed at physical modeling enhancements through implementation of polydispersity capability and validation of heat transfer models in MFIX. An extended verification and validation (V&V) study was performed for the new polydispersity feature implemented in MFIX-DEM both for granular and coupled gas-solid flows. The features of the polydispersity capability and results for an industrially relevant problem were disseminated through journal papers (one published and one under review at the time of writing of the final technical report). As part of the validation efforts, another industrially relevant problem of interest based on rotary drums was studied for several modes of heat transfer and results were presented in conferences. Third task was aimed towards an important and unique contribution of the project, which was to develop a unified uncertainty quantification framework by integrating MFIX-DEM with a graphical user interface (GUI) driven uncertainty quantification (UQ) engine, i.e., MFIX-GUI and PSUADE. The goal was to enable a user with only modest knowledge of statistics to effectively utilize the UQ framework offered with MFIX-DEM Phi to perform UQ analysis routinely. For Phase 1, a proof-of-concept demonstration of the proposed framework was completed and shared. Direct industry involvement was one of the key virtues of this project, which was performed through forth task. For this purpose, even at the proposal stage, the project team received strong interest in the proposed capabilities from two major corporations, which were further expanded throughout Phase 1 and a new collaboration with another major corporation from chemical industry was also initiated. The level of interest received and continued collaboration for the project during Phase 1 clearly shows the relevance and potential impact of the project for the industrial users.

42 ENGINEERING↗
DOE OSTI2021

Attend and Decode: 4D fMRI Task State Decoding Using Attention Models

Source code for Brain Attend and Decode paper. Functional magnetic resonance imaging (fMRI) is a neuroimaging modality that captures the blood oxygen level in a subject's brain while the subject either rests or performs a variety of functional tasks under different conditions. Given fMRI data, the problem of inferring the task, known as task state decoding, is challenging due to the high dimensionality (hundreds of million sampling points per datum) and complex spatio-temporal blood flow patterns inherent in the data. In this work, we propose to tackle the fMRI task state decoding problem by casting it as a 4D spatiotemporal classification problem. We present a novel architecture called Brain Attend and Decode (BAnD), that uses residual convolutional neural networks for spatial feature extraction and self-attention mechanisms for temporal modeling. We achieve significant performance gain compared to previous works on a 7-task benchmark from the large-scale Human Connectome Project-Young Adult (HCP-YA) dataset. We also investigate the transferability of BAnD's extracted features on unseen HCP tasks, either by freezing the spatial feature extraction layers and retraining the temporal model, or finetuning the entire model. The pre-trained features from BAnD are useful on similar tasks while finetuning them yields competitive results on unseen tasks/conditions.

Ng, BrendaM.↗
DOE OSTI2020

New Predictive Capabilities for Nuclear Weapons in Composite Fires

The prevalence of flammable carbon-based composite airframe materials and their use in high-temperature nuclear weapon re-entry systems requires analysts to address the abnormal thermal environment hazards associated with composite material fires. These fires tend to burn very differently than conventional fuel fires, usually burning less intensely, but much longer. This could lead to challenges in understanding margins in classic safety themes. The technical challenges in modeling the phenomena associated with these new types of fires are considerable, but new models have been developed. Their predictions have been compared with well-documented measurements of a vertical porous burner fire, known as a "wall fire" (a "wall-fire" validation simulation is reflected in the figures below). These measurements were conducted at FMGlobal, a mutual insurance company with a strong fire risk management program, as part of an ongoing collaboration between Sandia and FMGlobal. To date, the "wall-fire" scenario has been set up and initial model assessments with grid refinement studies have been conducted focusing on mesh resolutions suitable for full weapon system simulations. This work will continue with further verification and validation tasks assessing the predictions of the new model. Future work will address specific aspects of the wall models that are lacking in their predictive ability.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2015

Moving Toward Quantifying Reliability - The Next Step in a Rapidly Maturing PV Industry: Preprint

Some may say that PV modules are moving toward being a simple commodity, but most major PV customers ask: 'How can I minimize chances of a module recall?' Or, 'How can I quantify the added value of a 'premium' module?' Or, 'How can I assess the value of an old PV system that I'm thinking of purchasing?' These are all questions that PVQAT (the International PV Quality Assurance Task Force) and partner organizations are working to answer. Defining standard methods for ensuring minimal acceptable quality of PV modules, differentiating modules that provide added value in the toughest of environments, and creating a process (e.g. through IECRE [1]) that can follow a PV system from design through installation and operation are tough tasks, but having standard approaches for these will increase confidence, reduce costs, and be a critical foundation of a mature PV industry. This paper summarizes current needs for new tests, some challenges for defining those tests, and some of the key efforts toward development of international standards, emphasizing that meaningful quantification of reliability (as in defining a service life prediction) must be done in the context of a specific product with design parameters defined through a quality management system.

14 SOLAR ENERGY↗
DOE OSTI2024

IEA Wind TCP Task 55: The IEA Wind 740-10-MW Reference Offshore Wind Plants

This report describes the first version of the regular and irregular IEA-Wind 740-10MW Reference Offshore Wind Plants (v0.1). The two plants have been developed within the second work package of IEA Wind Task 37 on Wind Energy Systems Engineering: Integrated RD&D. The plants aim at acting as reference for future research projects on wind energy, representing modern offshore wind plants. The designs are based on the Borssele III and IV offshore wind plant projects. The associated wind resource, allotted territory, and bathymetry measurements are used to define the site characteristics. 74 IEA 10-MW Reference Wind Turbines are arranged in two suggested layouts that are optimized for maximum annual energy production: one regular grid layout, one irregular layout. These reference wind plants have been described using the WindIO ontology and have been made available through an open-source repository on GitHub.

17 WIND ENERGY↗
DOE OSTI2026

FAD-Toolset (Floating Array Design Toolset) [SWR-26-056]

The Floating Array Design (FAD) Toolset is a collection of tools for modeling and designing arrays of floating offshore structures. It was originally designed for floating wind systems but has applicability for many offshore applications. A core part of the FAD Toolset is the floating array model, which serves as a high-level library for efficiently modeling a floating array, such as a floating wind array. It combines site condition information and a description of the floating array design, and contains functions for evaluating the array's behavior considering the site conditions. For example, it combines information about site soil conditions, mooring line loads, and an array's anchor characteristics to estimate the holding capacity of each anchor. The library works in conjunction with the tools RAFT, MoorPy, and FLORIS to model floating platforms, wind turbines, mooring systems, power cables, and array wakes respectively. Layered on top of the floating array model is a set of design tools that can be used for algorithmically adjusting or optimizing parts of the a floating array. Specific tools existing for mooring lines, shared mooring systems, dynamic power cables, static power cable routing, and overall array layout. These capabilities work with the design representation and evaluation functions in the floating array model, and they can be applied by users in various combinations to suit different purposes. In addition to standalone uses of the FAD Toolset, a coupling has been made with Ard, (https://github.com/NLRWindSystems/Ard) a sophisticated and flexible wind farm optimization tool. This coupling allows Ard to use certain mooring system capabilities from FAD to perform layout optimization of floating wind farms with Ard's more advanced layout optimization capabilities. The FAD Toolset works with the IEA Wind Task 49 Ontology (https://github.com/IEAWindTask49/Ontology), which provides a standardized format for describing floating wind farm sites and designs. See example use cases in our examples folder (https://github.com/NLRWindSystems/FAD-Toolset/blob/main/examples/README.md) For working with the library, it is important to understand the floating array model structure, which is described more here: https://github.com/NLRWindSystems/FAD-Toolset/blob/main/fad/README.md.

Sirkis, Leah [National Laboratory of the Rockies (↗
DOE OSTI2019

IEA Wind TCP Task 37: Systems Engineering in Wind Energy - WP2.1 Reference Wind Turbines

This report describes two wind turbine models developed within the second work package (WP2) of IEA Wind Task 37 on Wind Energy Systems Engineering: Integrated RD&D. The wind turbine models aim at acting as references for future research projects on wind energy, representing a modern land-based wind turbine and a next generation offshore wind turbine. The land-based design is a class IIIA geared configuration with a rated electrical power of 3.4-megawatts, a rotor diameter of 130 meters (m), and a hub height of 110 m. The offshore design is a class IA configuration with a rated electrical power of 10.0 megawatts, a rotor diameter of 198 m, and a hub height of 119 m. The offshore turbine adopts a direct-drive generator.

17 WIND ENERGY↗
DOE OSTI2020

Advanced Wind Turbine Drivetrain Topology for Improving System Reliability (CRADA CRD-10-400 Final Report)

Alstom Power has a desire to locate its latest entrance into the U.S. market at a location that truly tests the durability of the machine in a turbulent environment as well as verify the basic operating characteristics of the machine on a 60 Hz grid. The DOE/NREL National Wind Technology Center (NWTC) is well suited for this goal. The DOE/NREL Wind Program is working on improving drivetrain reliability through its Gearbox Reliability Collaborative (GRC). Alstom is also interested in performing research on their innovative drivetrain that is aligned with the objectives of the GRC. The tasks outlined in this Joint Work Statement are intended to accomplish these goals to the mutual satisfaction of both parties and the advancement of the understanding of wind turbine drivetrain behavior.

17 WIND ENERGY↗
DOE OSTI2012

Data-driven Fault Tolerance for Work Stealing Computations

Checkpoint-restart approaches to fault tolerance typically roll back all the processes to the previous checkpoint in the event of a failure. Work stealing is a promising technique to dynamically tolerate variations in the execution environment, including faults, system noise, and energy constraints. In this paper, we present fault tolerance mechanisms for task parallel computations, a popular computation idiom, employing work stealing. The computation is organized as a collection of tasks with data in a global address space. The completion of data operations, rather than the actual messages, is tracked to derive an idempotent data store. This information is used to accurately identify the tasks to be re-executed, therefore to recompute only the lost data, in the presence of random work stealing. We consider three recovery schemes that present distinct trade-offs -- lazy recovery with potentially increased re-execution cost, immediate collective recovery with associated synchronization overheads, and noncollective recovery enabled by additional communication. We employ distributed work stealing to dynamically rebalance the tasks on the live processes and evaluate the three schemes using candidate application benchmarks. We demonstrate that the overheads (space and time) of the fault tolerance mechanism are low, the cost incurred due to failures are small, and the overheads decrease with per-process work at scale.

fault tolerance, task parallelism, load balancing,↗
DOE OSTI2022

Semi-Annual Report for Modular Integrated Gas High Temperature Reactor Development during Performance Period October 2021 - March 2022

Modular Integrated Gas High Temperature Reactor (MIGHTR) is being designed by a multidisciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed MIGHTR in 3 years and support its commercialization as a safe and low-cost HTGR. Argonne National Laboratory is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Work performed by Argonne also includes the thermal hydraulics analysis of the primary heat transport system including reactor pressure vessel (RPV) internals for normal operation, shutdown, and accident conditions. This first semi-annual report summarizes the progress made at Argonne on the two tasks since the start of the project. For the RCCS design task, high-level design work was performed including identification of design requirements for the conceptual MIGHTR RCCS and initial design calculations. The baseline dimensions of the MIGHTR RCCS were derived from scoping analysis results and preliminary steady state performance was estimated. At the initial stage of the primary system analysis task, the primary system thermal fluids model for the MIGHTR core was outlined to use a simplified two-dimensional model to predict the temperature distribution and coolant pressure losses in the fuel assembly blocks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Application of Pulse Spark Discharges for Scale Prevention and Continuous Filtration Methods in Coal-Fired Power Plant

The overall objective of the present work was to develop a new scale-prevention technology by continuously precipitating and removing dissolved mineral ions (such as calcium and magnesium) in cooling water while the COC could be doubled from the present standard value of 3.5. The hypothesis of the present study was that if we could successfully precipitate and remove the excess calcium ions in cooling water, we could prevent condenser-tube fouling and at the same time double the COC. The approach in the study was to utilize pulse spark discharges directly in water to precipitate dissolved mineral ions in recirculating cooling water into relatively large suspended particles, which could be removed by a self-cleaning filter. The present study began with a basic scientific research to better understand the mechanism of pulse spark discharges in water and conducted a series of validation experiments using hard water in a laboratory cooling tower. Task 1 of the present work was to demonstrate if the spark discharge could precipitate the mineral ions in water. Task 2 was to demonstrate if the self-cleaning filter could continuously remove these precipitated calcium particles such that the blowdown could be eliminated or significantly reduced. Task 3 was to demonstrate if the scale could be prevented or minimized at condenser tubes with a COC of 8 or (almost) zero blowdown. In Task 1, we successfully completed the validation study that confirmed the precipitation of dissolved calcium ions in cooling water with the supporting data of calcium hardness over time as measured by a calcium ion probe. In Task 2, we confirmed through experimental tests that the self-cleaning filter could continuously remove precipitated calcium particles in a simulated laboratory cooling tower such that the blowdown could be eliminated or significantly reduced. In addition, chemical water analysis data were obtained which were used to confirm the COC calculation. In Task 3, we conducted a series of heat transfer fouling tests using a condenser heat exchanger in the laboratory cooling tower, from which we confirmed that the plasma water treatment technology could prevent or significantly mitigate mineral foulings in condenser tubes when compared with the no-treatment case. With the completion of the present work, a cooling water treatment technology using pulse spark discharges is currently ready for field-validation tests. The plasma water treatment technology is a true mechanical water softener with almost no maintenance, which continuously converts hard water to soft water spending a relatively small amount of energy. Such a mechanical water softener could find wide-spread applications to solve hard water problems both in industry and at home.

20 FOSSIL-FUELED POWER PLANTS↗