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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Bridging Equipment Reliability Data and Robust Decisions in a Plant Operation Context

In order to reduce operation and maintenance (O&M) costs, nuclear power plants (NPPs) are moving from corrective and periodic maintenance to predictive maintenance strategies. Such transition requires changes on the data that needs to be retrieved and on the type of decision processes to be employed. Advanced monitoring and data analysis technologies are essential to support predictive strategies. They can in fact provide precise information about health of a component, track its degradation trends, and provide information of its expected failure time. With such information, maintenance operations for a component can be performed right before its expected failure time. This dynamic context of O&M operations requires new methods to analyze data, propagate component health information from the component to the system level, and optimize plant resources. In this respect, the risk informed asset management (RIAM) project has been tasked to develop and test this new class of methods into a risk analytics toolset. This toolset consists of data analytics tools coupled with reliability methods designed to manage plant assets and performances in a predictive maintenance context. This report shows the latest improvements on such development and the initial testing of our methods on the three main research areas that the RIAM project is focusing on. These areas are the following: equipment reliability data analytics, system reliability modeling, and plant resources optimization methods. We show how the methods developed in these areas can support predictive maintenance strategies by: 1) analyzing equipment reliability data (either in numeric and textual form), 2) assessing component and system health through an innovative margin-based reliability approach, and 3) identifying the most critical components and set optimal maintenance schedule based on plant economic and operational constraints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

An Investigation of Strategies for Sensing Window Attachment Position: Survey of Candidate Technologies, Evaluation, and Deployment Recommendations

While windows are desirable feature in buildings for views, daylighting, and aesthetics, it is important to recognize that windows are a major contributor to a building’s energy load. Interior window coverings, such as shades and blinds, can help improve the energy performance of windows without sacrificing the benefits; however, while appropriate use of window coverings provide the potential for energy savings, there is little consensus regarding how occupants typically use these window attachments, which sometimes puts into question how much energy they actually save in an occupied home. Automated shading control strategies can reduce the uncertainty of energy savings; however, users can overwrite pre-defined schedules or write their own shade control programs to reach their personal comfort and privacy goals. Because it is difficult to identify how occupants interact with window shades, it is difficult to identify the energy savings potential of blinds. To address this problem, this study was developed to identify a candidate sensor that can be deployed to sense blind position. The intended application for this sensor is deployment in energy efficiency field studies so that shade usage can be measured to better understand results and identify the energy impact of specific window attachment technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Prototype energy models for data centers

Data centers in the United States consume about two percent of the nation’s electricity. Because heat gains from IT equipment drive cooling demand, data centers offer unique opportunities for energy savings. However, no prototype energy model for data centers is available in the suite of existing U.S. Department of Energy’s Commercial Prototype Building Models. Here we present the development of two new data center prototype models and their implementation in OpenStudio and EnergyPlus. The small-size data center model represents a computer room in a building served by computer room air conditioners (CRACs); while the large-sized model represents stand-alone data centers served by computer room air handlers (CRAHs) with a central chiller plant. For each data center model, two levels of IT equipment (ITE) load density were considered, to cover the wide range of IT power density of data centers: 40 and 100 W/ft 2 (430 and 1076 W/m 2 ) for the computer room, and 100 and 500 W/ft 2 (1076 and 5382 W/m 2 ) for the stand-alone data center. All other assumptions, such as building envelope, lighting, HVAC efficiencies and schedules, were based on the minimal requirements of ASHRAE Standard 90.1 at various vintages. We introduced a novel concept of supply and return air approach temperatures to capture the essential effects of non-uniform airflow and temperature distribution in data centers. The approach temperatures were pre-computed by computational fluid dynamics (CFD) simulations for various configurations of ITE loads and airflow containment management in data centers. A new feature was developed in EnergyPlus to implement the approach temperature method. A case study was conducted to demonstrate the use of the data center models. The two data center models cover all U.S. climate zones and can be used to evaluate energy saving measures for data centers, as well as to support development of data center energy efficiency codes and standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Safe Deep Reinforcement Learning for Active Distribution System Model Predictive Control with EVs and DERs

The temporal and spatial mismatch between PV generation and electric vehicle (EV) charging and discharging may cause voltage violations in active distribution networks. Despite the widespread use of deep reinforcement learning (DRL) in power system optimization and control, it lacks guarantees on constraint satisfaction during both training and deployment. This paper proposes a Lagrangian-based safe DRL approach for model predictive control (MPC) of active distribution systems with large-scale integration of PVs, EVs, and energy storage systems (ESSs). A Transformer-LSTM time-series model is proposed to forecast EV charging demand, which is then formulated as a constraint to ensure charging requirements are met. Using this prediction, a Lagrangian-based safe soft actor-critic (SAC) framework is developed for real-time control in a three-phase unbalanced distribution system, enforcing voltage safety constraints while optimizing the cumulative net reward. By integrating the forecasting model with multi-period constraints, the proposed framework jointly coordinates PV systems, EV charging and discharging, and ESS scheduling within the MPC horizon. Numerical experiments on a modified IEEE 123-bus system with real-world data show that, under a high PV penetration scenario, the proposed method increases the net reward by 30.74% and reduces average voltage violations from 0.0011 p.u. to 0.0002 p.u. compared with standard SAC. Compared with the optimal power flow (OPF) approach, it achieves similar voltage security while yielding lower line losses. It also maintains real-time control capability, reducing operation latency to 53.21 ms per 15-minute control interval. The proposed method remains effective under varying PV/EV penetrations and load conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A 32-channels readout ASIC for X-ray spectrometry and tracking in the GAPS experiment

Here this work describes the architecture and the experimental results from the characterization of a 32-channels mixed-signal Application-Specific Integrated Circuit (ASIC) developed for the readout of the lithium-drifted silicon, Si(Li), detectors of the General AntiParticle Spectrometer (GAPS) experiment dedicated to searching for dark matter. The instrument is designed for the identification of antiprotons, antideuterons and antihelium nuclei from cosmic rays during an Antarctic balloon mission scheduled for late 2024. A full custom integrated circuit, named SLIDER32 (32-channels Si-LI DEtector Readout) ASIC, has been produced in a commercial 180 nm CMOS technology. The ASIC is comprised of 32 low-noise analog readout channels featuring dynamic signal compression to comply with the wide input range, an 11-bit SAR ADC and a digital back-end section which is responsible for channel setting and for sending digital information to the data acquisition system (DAQ). The circuit design criteria and the experimental results are discussed in the paper.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Hydrogen from Carbonaceous Waste Material - Hydrogen Fuel Cells Prize Phase 2 Voucher: Cooperative Research and Development (Final Report)

NLR conducted a conceptual design study for scaling up biomass conversion technology from Green Fortress Engineering (GFE). GFE has proprietary technology where cellulosic biomass is thermally converted to a tar-free syngas. A ceramic membrane separation unit (MSU) previously developed with NLR can extract high-purity hydrogen from the syngas. The energy content of the retentate stream is sufficient to power the process with a gas-powered genset. Design details including mass and energy balances, process and instrumentation diagrams (P&ID), and major equipment schedules were delivered.

08 HYDROGEN↗
DOE OSTI2023

Online Monitoring of Medium Voltage Cable Systems with Spread Spectrum Time Domain and Frequency Domain Reflectometry

In-service failures of wave energy convertor (WEC) cable systems can have a significant cost and power availability impact. Close parallel research 2019 data showed > 1B£ and 9 Terra-Watt-Hours associated with global off-shore wind (OSW) cable failures (Strang-Moran 2020). OSW is a closely related technology but currently is significantly cheaper than WEC technology. For wave energy to compete, the problem of reliable cable transmission must be mitigated. This project develops isolation technology to allow online high frequency reflectometry testing of medium voltage cables (1 to 10 kV and higher) without arcing or damage to the test instrument. Online spread spectrum time domain reflectometry (SSTDR) testing has been established for low voltage cable systems in the aircraft and rail industry and the ability to detect and locate cable flaws of interest is well understood. Extending reflectometry testing to medium voltage systems could enable detection of cable damage before failures occur thereby allowing repair and replacement of damaged cable segments to be scheduled and managed. The seedling project succeeded to pass and receive high frequency SSTDR signals onto a cable up to 1 kV using a parallel trace isolation circuit board that can be connected onto the test cable. The approach used a novel circuit design for which an invention disclosure has been filed. A proposed sapling project would extend the technology toward the higher operating voltages used by WEC systems, thereby enabling online SSTDR cable monitoring. The goal of the seedling project was to extend the capability of the ARENA cable/motor test bed to address medium voltages and to develop a high pass filter isolation architecture to protect the reflectometry instrument from the low frequency (DC – 60 Hz) line voltage while allowing the high frequency diagnostic signal to pass to and from the test instrument to the live line. Initial efforts focused on passive LCR filter circuits to reduce 60 Hz levels below 10 volts from a 10 kV line while allowing the MHz high frequency chirps to pass onto the cables and for mV signals to be detected. We discovered that the parasitic loss behavior of real high voltage components precluded this approach from working. An alternate approach was adapted for the electric field to couple between two parallel traces on a printed circuit board much like a radio-frequency coupler. The challenge here was and is to have the parallel traces close enough to each other to effectively pass the high frequency chirp onto the live line and receive any reflected signal from any encountered impedance change along the cable. This reflected signal will be in the mV range. The traces however must be far enough apart to not allow arcing on the board. A design with 3 mm spacing was determined to allow the high frequency signal to pass onto the live line and receive the mV signal back into the instrument while reducing the 60 Hz voltage amplitude by >80 dB (more than a factor of 10,000) without allowing arcing from across the parallel traces. This was confirmed by simulation and test.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Analysis of different operating strategies of thermal energy storage with radiant cooling system

Thermal energy storage systems in building cooling applications have been explored extensively as a peak load-shifting technology. Thermal energy storage performance has been recognized and studied from an energy cost-savings point of view because of peak-valley price differences, but not many studies have been conducted from an energy savings viewpoint. This study experimentally investigates the performance of the energy storage-retrofitted to a ceiling-type radiant cooling system. To study the performance, a water-based storage system was designed and developed for an academic office building equipped with a radiant cooling system. The water in the storage tank was cooled to a certain storage temperature in the nighttime, and the same water was used during the daytime for meeting the cooling load. Different combinations of charging and discharging schedules were analyzed. The key objective of the study was to achieve energy savings and energy-cost savings simultaneously. This objective was accomplished by identifying the major factors contributing to the energy consumption of the storage-retrofitted cooling system and devising novel operating strategies, leading to an enhanced energy savings potential. Two operating strategies comprising 24 operating scenarios were compared and the storage was used to dispatch the load for 3 hours of the day as a full storage unit. Results showed that in hot and dry climate conditions, using the storage with the radiant cooling system offered energy savings of 3% to 14%. The energy-cost analysis was also performed using a time-of-day electricity tariff plan. The energy-cost savings varied from 17.5% to 22.4% for these operating scenarios.

25 ENERGY STORAGE↗
DOE OSTI2022

Tracking Volumetric Units in Modular Factories for Automated Progress Monitoring Using Computer Vision

The construction industry is increasingly adopting off-site and prefabricated methods due to advantages offered in safety, quality, and lead time. Applying industrialized methods for plant management in offsite construction factories requires the collection of large volumes of production process data, which is a tedious task when performed manually. Recent attempts to automate this process have relied on sensor-based data collection methods which are susceptible to noise, expensive, and difficult to validate. Computer vision methods, however, enable process data collection from videos without the limitations of the other sensor-based methods. This technology has not been applied for offsite construction except in very few instances and therefore, this study proposes a novel method to reliably collect the production process data using computer vision method in near real-time from widely used surveillance cameras in offsite construction. The proposed method allows the user to annotate the workstations of interest on the video as ground truths and process these areas throughout the entire video to track the units entering and leaving stations, while continuously updating a near real-time schedule of the production line. This framework was validated by implementing on the surveillance videos of the production process of modular home manufacturing in a factory. The results consistently provided 100% accuracy, after denoising, for all the videos processed including 60 h of work for a station. The developed method enables real-time tracking of station performance, which can enable continuous improvement methods for factory management and resource allocation.

computer vision↗
DOE OSTI2024

Digital-Twin-Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable optimized scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins (DTs) are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. DTs for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. A DT’s goal is to provide additional insights by combining and interpreting various sources of information for preventative maintenance scheduling optimization or early fault detection. DTs for condition monitoring are projected to be valuable for meeting requirements under 10 CFR 50.55a, “Codes and Standards,” and 10 CFR 50.65, “Requirements for Monitoring the Effectiveness of Maintenance at Nuclear Power Plants”. However, DT technologies are still under significant development, and the process for developing a DT for condition monitoring has not been formalized. Therefore, in this work, we present an initial framework for developing a DT, discuss and review the various challenges and considerations for DT deployment, and identify the opportunities that a DT can improve. The presented framework is intended to help developers formulate a strategy when approaching DT development for condition monitoring. In conclusion, a DT use case for a reactor coolant pump is presented to demonstrate the proposed framework.

advanced sensor instrumentation↗
DOE OSTI2020

STEP Report on Advanced ODS FeCrAl Alloys for Fission Applications

Oak Ridge National Laboratory is developing advanced low-Cr oxide dispersion strengthened (ODS) FeCrAl alloys for accident tolerant fuel (ATF) cladding. This report presents the characterization of two new ODS FeCrAl tubes by using powder commercially mechanically alloyed by Zoz GmbH, which underwent high-precision tube rolling with two different annealing schedules. This work shows that the ODS FeCrAl tube without recrystallization exhibits consistent mechanical behavior in comparison with a previously produced tube. The second tube, which underwent a full recrystallization step before the final tube rolling step, showed some circumferential cracking and exhibited limited ductility in the axial tube tensile tests. Based on current and prior work on the ODS FeCrAl alloy system, this report compares the current state of the scientific literature on the alloy class with that of wrought FeCrAl without oxide additions. Then, this report makes recommendations for future research directions that should be undertaken to increase the technology readiness level for ODS FeCrAl as a viable ATF candidate material. This report has been submitted as fulfillment of milestone M3FT-20OR020202064 titled, “STEP Report on Advanced ODS FeCrAl Alloys for Fission Applications” for the US Department of Energy Office of Nuclear Energy’s Advanced Fuel Campaign of the Fuel Cycle R&D program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Experiments to Measure the Effect of Tantalum on Critical Systems

Sandia National Laboratories (SNL) and Oak Ridge National Laboratory (ORNL) collaborated to develop a capability to test the epithermal/intermediate cross sections of materials at the SNL critical experiment facility using the Seven Percent Critical Experiment (7uPCX) fuel. As a result, a new set of critical experiments has been designed to target the epithermal cross sections of tantalum (Ta) and is scheduled to be performed at SNL in 2023. These critical experiments will be evaluated for inclusion in the 2024 edition of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The focus of these critical experiments is to measure the effects of Ta on the critical array size. The critical array size will be determined by an approach-to-critical experiment with the number of fuel rods in the array as a free parameter. The core configurations are designed to optimize the reactivity worth of Ta and the overall percentage of Ta absorption rates in the epithermal/intermediate energy range (0.625 eV – 100 keV). The baseline core configuration includes 7uPCX fuel rods set at a triangular pitch of 1.016 cm and a central dry test region that utilizes a cadmium liner for filtering out thermal neutrons. The central test region has locations for 85 Ta rods set at a triangular pitch of 0.813 cm. The Ta reactivity worth for the case with 85 Ta rods is approximately 2.55%, with the percentage of Ta absorption rates within the intermediate energy range at nearly 90%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Waste Information Management System with 2019-20 Waste Streams - 20491

The Waste Information Management System (WIMS) 2019-20 was updated to support the Department of Energy (DOE) accelerated cleanup program. The schedule compression required close coordination and a comprehensive review and prioritization of the barriers that impeded treatment and disposition of the waste streams at each site. Many issues related to waste treatment and disposal were potential critical path issues under the accelerated schedule. In order to facilitate accelerated cleanup initiatives, waste managers at DOE field sites and at DOE Headquarters in Washington, D.C., needed timely waste forecast and transportation information regarding the volumes and types of radioactive waste that would be generated by DOE sites over the next 35 years. Each local DOE site historically collected, organized, and displayed waste forecast information in separate and unique systems. In order for interested parties to understand and view the complete DOE complex-wide picture, the radioactive waste and shipment information of each DOE site needed to be entered into a common application. The WIMS application was therefore created to serve as a common application to improve stakeholder comprehension and improve DOE radioactive waste treatment and disposal planning and scheduling. WIMS allows identification of total forecasted waste volumes, material classes, disposition sites, choke points, technological or regulatory barriers to treatment and disposal, along with forecasted waste transportation information by rail, truck and intermodal shipments. The Applied Research Center (ARC) at Florida International University (FIU) in Miami, Florida, developed and deployed the web-based forecast and transportation system and is responsible for updating the radioactive waste forecast and transportation data on a regular basis to ensure the long-term viability and value of this system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Shaping the FutureWorkforce: Challenges and Lessons Learned in HPC Education from National Labs and Computing Centers

Workforce training at national laboratories and computing centers is essential and typically falls into two categories: foundational training for newcomers and advanced training for experienced users. Foundational topics—such as version control, build systems, and basic HPC usage—are largely transferable across institutions, while cluster-specific training varies due to differences in hardware, job schedulers, and local workflows. Training on emerging technologies is split between hardware-specific content and broadly applicable programming paradigms. Here, to reduce redundancy and increase impact, national labs, computing centers, and vendors are collaborating through initiatives like the HPC Training Working Group to share best practices, co-develop materials, and broaden outreach. These coordinated efforts aim to make HPC training more accessible, scalable, and consistent across the community.

HPC↗
DOE OSTI2020

Wall Upgrades for Deep Energy Savings in Residential Buildings: Interim Results from a Multi-Year Study

The Pacific Northwest National Laboratory, Oak Ridge National Laboratory and the University of Minnesota are conducting a three-year, multipart study on residential retrofit wall assemblies. The project is funded by the U.S. Department of Energy’s Building Technology Office and will identify, test and verify wall assemblies for hygrothermal performance in retrofit applications. The study includes a comprehensive literature review and expert advisory group, which inform wall selection. Selected wall assemblies are then thermally simulated using EnergyPlus and THERM, and hygrothermally simulated using WUFI, to model both thermal and moisture performance of the wall assembly. Eight wall assemblies are then experimentally tested in an in-situ laboratory environment at the University of Minnesota, with a typical residential wall used as a baseline. The in-situ experiment looks at the physical hygrothermal performance of each assembly. The simulation and experimental results will be combined with an economic analysis to produce a techno-economic study of residential wall systems for deep energy retrofits. This paper presents progress after year one of the study. Wall system modeling and laboratory testing is scheduled to begin in November, 2019. We will discuss the parameters for wall selection and experimental design, which includes approaches to modeling and simulation, along with the physical experiment design. This paper will also outline the parameters for the techno-economic analysis, and criteria used to inform model development.

Antonopoulos, Chrissi A.↗
DOE OSTI2022

An energy storage dispatch optimization for demand-side management in industrial facilities

An energy storage (ES) dispatch optimization was implemented to test lithium-ion battery ES, supercapacitor ES, and compressed air ES on two different industrial facilities – one intermittent process facility and one continuous process facility. The model first shows the capability of optimizing the size of a single technology on a single industrial facility to maximize the return on investment. Then, for the same profile, the model identifies significant differences in the optimal size for different technologies based on their performance parameters. Third, the model identifies differences in the optimal size for each technology based on the facilities profile. Here the results show compressed air ES yields the highest return on investment for both facilities and provides insight for future development of ES systems.

25 ENERGY STORAGE↗
DOE OSTI2022

Low-GWP Refrigerants Status and Outlook

Refrigeration - including air conditioning (AC) – contributes substantially to the modern life of the 21st century and its economy. The food cold chain, air conditioning, healthcare and energy are examples of sectors for which refrigeration is indispensable. About 5 billion refrigeration systems – of different types and sizes– operate worldwide in different applications [1]. The dominant share of equipment providing refrigeration operate on the vapor-compression-cycle principle and use fluorocarbon refrigerants. Concerns about the environmental safety have become the driving force for refrigerant changes within the last 35 years. The phased-out schedule of stratospheric-ozone-depleting fluids was first formulated by the Montreal Protocol (MP) in 1987 and was made more stringent during the follow-up international meetings [2]. The affected chlorofluorocarbon (CFC) and hydrochlorofluorocarbon (HCFC) refrigerants were largely replaced by hydrofluorocarbons (HFCs).The 2016 Kigali Amendment to the MP [3] responses to the concerns about the Earth climate change. The refrigeration and AC sectors are attributed with about 7.8 % of global greenhouse gas emissions [4]. This contribution comes in the form of direct effect, which is related to refrigerant emissions from refrigeration systems (37 %), and in the form of indirect effect, which is related to CO2 emissions from fossil fuel power plants producing electricity to power refrigeration systems (63 %) [4]. The Kigali Amendment aims at reducing the direct effect. The effect a given molecule has on the climate change is quantified in a simplified manner by its Global Warming Potential (GWP), a relative index referencing the effect produced to that of the same mass of carbon dioxide released to the atmosphere. By definition, GWP of carbon dioxide is equal to one.While HFC refrigerants have on average a lower GWP than the CFCs and HCFCs they replaced, they are still potent greenhouse gases (GHGs). The Kigali Amendment phases down the use of HFCs by imposing a schedule for reducing a weighted GWP value to be implemented by a country through the year 2047 (Figure 1). It provides four paths depending on the country location and category assigned in the MP, and also prescribes a method for establishing the baseline consumption used for calculating GWP reductions. For developing countries, it is expected to bring the weighed GWP across all refrigeration applications down to about 300 from the baseline value of about 2000. The implementation of Kigali Amendment aims at reducing the future warming due to HFCs from the range of 0.3 °C to 0.5 °C to less than 0.1 °C [5]. While this reduction may seem to be small, it must be viewed in the context of the 2015 Paris Agreement [6], which calls for holding global warming to well below 2 °C and pursuing to limit global warming to 1.5 °C relative to pre-industrial levels [6]. Considering that average global temperatures reached 1 °C above pre-industrial levels for the first time in 2015 [7], the Earth is already within 1 °C of the “2 °C limit”.The low-GWP requirement narrows the pool of fluids that can be considered for application as a refrigerant [8]. This Informatory Note discusses low-GWP refrigerant options for major applications and presents their selection merits.

Yana Motta, Samuel↗
DOE OSTI2021

Optimal Energy Scheduling and Sensitivity Analysis for Integrated Power-Water-Heat Systems

The conventionally independent power, water, and heating networks are becoming more tightly connected, which motivates their joint optimal energy scheduling to improve the overall efficiency of an integrated energy system. However, such a joint optimization is known as a challenging problem with complex network constraints and couplings of electric, hydraulic, and thermal models that are nonlinear and nonconvex. We formulate an optimal power-water-heat flow (OPWHF) problem and develop a computationally efficient heuristic to solve it. The proposed heuristic decomposes OPWHF into subproblems, which are iteratively solved via convex relaxation and convex-concave procedure. Simulation results validate that the proposed framework can improve operational flexibility and social welfare of the integrated system, wherein the water and heating networks respond as virtual energy storage to time-varying energy prices and solar photovoltaic generation. Moreover, we perform sensitivity analysis to compare two modes of heating network control: by flow rate and by temperature. Our results reveal that the latter is more effective for heating networks with a wider space of pipeline parameters.

24 POWER TRANSMISSION AND DISTRIBUTION↗