Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Operational Reliability”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High CO2 Capture Rate Cost and Performance for F- and H-Class Natural Gas Combined Cycles (NGCC)

The National Energy Technology Laboratory (NETL) is updating its study titled “Cost and Performance Baselines for Fossil Energy Plants, Volume 1: Bituminous Coal and Natural Gas to Electricity.” Revision 4 was published in 2019. Pulverized coal (PC) and natural gas combined cycle (NGCC) cases with carbon capture in that study capture carbon dioxide (CO2) at 90% efficiency. Field-testing of post-combustion CO2 capture technology as well as vendor and industry feedback on projects currently in the planning stages (including FEED projects sponsored by DOE) indicate that capture rates as high as 95% are feasible for both coal- and natural gas-fueled electricity generating units. Technology suppliers (as reflected in vendor-supplied information provided to DOE for this study that included cost and performance estimates for both NGCC (97%) and PC (99%) study cases) as well as subject matter experts acknowledge and support that solvent-based post-combustion CO2 capture technologies are capable of achieving CO2 removal rates beyond 95% on low-purity streams representative of fossil-fueled combustion; however, the relatively limited experience with design and operation of capture systems that can routinely, reliably, and economically achieve very high removal rates (e.g., 97% for NGCC flue gas) requires further study. This presentation will address performance and cost estimates for 90%, 95%, and 97% capture for F- and H-class NGCC plants. This presentation was given at the 2022 Pittsburgh Coal Conference.

Fout, Timothy↗
DOE OSTI2025

Ship Motion Testing Needs Evaluation

The American Bureau of Shipping performed an evaluation of national maritime nuclear testing capabilities and determined there currently is an inability to test maritime nuclear power plants in a ship motion environment. A Ship Motion Test Facility (SMTF) is proposed to fill this gap. To inform design of this facility, this report documents an evaluation performed by a panel of technical experts that identifies key physical phenomena associated with maritime nuclear power plant operation that are important to safety and reliability and have a low state of knowledge. This evaluation concluded that all of the major test needs to understand a nuclear plant's behavior in a ship motion environment are for thermal-hydraulics related phenomena. Based on this finding, the evaluation panel concluded that the SMTF would not be required to use nuclear fuel to provide a heat source for the fluids. This would significantly decrease the cost, timeline, and complexity for this test facility to enable the advancement of maritime nuclear technology.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Hybrid Analytics Solution for Power Plant Operations

Expert Microsystems, Inc., MapEx Software Inc. and XMPLR Energy LLC have teamed to submit a proposal to the US Department of Energy’s Office of Fossil Energy to improve the efficiency, reliability and flexibility of existing coal-based power plants. The project, titled Hybrid Analytics Solution to Improve Coal Power Plant Operations (the “Hybrid Analytics” project), will develop, demonstrate and commercialize a novel approach that integrates two proven real-time monitoring techniques. The Hybrid Analytics approach integrates into a single, integrated solution: a) an established, advanced data-driven analytics solution that includes artificial intelligence, advanced pattern recognition and machine-learning techniques and b) a well-proven, first principle thermal heat balance model solution. The future role of coal plants will depend on the ability to cycle and follow loads to meet marginal power demands, accommodate renewables and support the grid. Essential to success in this new role is a plant’s ability to maintain high reliability, efficiency and flexibility. However, these changing operational demands put significant stresses on power plant components that directly impact the ability to deliver these requirements. In the past, plants have independently monitored performance using physics-based solutions (heat rate, boiler losses, etc.) and reliability using data-driven analytics (advanced pattern recognition). The Hybrid Analytics solution integrates both approaches to enhance fault detection, provide automated diagnostics and estimates of remaining time to act, and provide critical, enhanced and accurate real-time information to coal plant operators. As a result, coal plants can improve efficiency, reliability, and flexibility and can cost-effectively maintain their key role in the power delivery system.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Integrating Variable Renewable Energy Into the Grid: Key Issues

To foster sustainable, low-emission development, many countries are establishing ambitious renewable energy targets for their electricity supply. The variability of solar and wind compared to traditional sources, coupled with growing demand for electricity, requires changes to power system planning and operations to meet these targets. Grid integration is the practice of developing efficient ways to deliver variable renewable energy (VRE), primarily wind and solar, to the grid. Good integration methods maximize the cost-effectiveness of incorporating VRE while maintaining or increasing system stability and reliability. To inform decarbonization strategies, policymakers, regulators, and system operators consider a variety of costs and opportunities associated with VRE integration, which can be organized into five topics: New renewable energy generation and transmission; Power system reliability; Transmission and distribution coordination; Cross-sectoral decarbonization opportunities; Energy equity and justice.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Implementation of WBG devices in circuits - Electric Drive Technologies Project (Final Technical Report)

The objective of the project is to ensure that SiC devices are reliable and rugged as required in automotive applications for operational life of 300,000 hrs and create new device designs to address various weaknesses in currently available commercial devices. OSU has worked closely with SUNY Polytechnic. OSU has carried out the reliability and ruggedness evaluations of commercial devices as well as those fabricated by SUNY Polytechnic, discussed the results with SUNY Poly, and collaborated with the PI at SUNY Poly to improve the designs with respect to reliability/ruggedness. OSU work focused on reliability/ruggedness evaluation of SiC devices by individually testing them and then evaluate them in a 10 kW, 3 phase inverter system built with a specific purpose of stressing devices using realistic drive cycles such as a 10-minute hill climb. It should be noted that the primary purpose of the 10 kW inverter is to provide a platform for stressing the SiC devices under accelerated but realistic drive conditions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Models Integrated in Instrumentation & Control Systems

In recent years, the field of data-driven neural network-based machine learning (ML) algorithms has grown significantly and spurred research in its applicability to instrumentation and control systems. While they are promising in operational contexts, the trustworthiness of such algorithms is not adequately assessed. Failures of ML-integrated systems are poorly understood; the lack of comprehensive risk modeling can degrade the trustworthiness of these systems. In recent reports by the National Institute for Standards and Technology, trustworthiness in ML is a critical barrier to adoption and will play a vital role in intelligent systems' safe and accountable operation. Thus, in this work, we demonstrate a real-time model-agnostic method to evaluate the relative reliability of ML predictions by incorporating out-of-distribution detection on the training dataset. It is well documented that ML algorithms excel at interpolation (or near-interpolation) tasks but significantly degrade at extrapolation. This occurs when new samples are "far" from training samples. The method, referred to as the Laplacian distributed decay for reliability (LADDR), determines the difference between the operational and training datasets, which is used to calculate a prediction's relative reliability. LADDR is demonstrated on a feedforward neural network-based model used to predict safety significant factors during different loss-of-flow transients. LADDR is intended as a "data supervisor" and determines the appropriateness of well-trained ML models in the context of operational conditions. Ultimately, LADDR illustrates how training data can be used as evidence to support the trustworthiness of ML predictions when utilized for conventional interpolation tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

DEVELOPMENT AND APPLICATION OF RISK ANALYSIS TOOLKIT FOR PLANT RESOURCE OPTIMIZATION

This paper presents the development of methods and tools that are being designed to optimize plant operations (e.g., maintenance/replacement schedules and optimal maintenance postures for plant components) in a manner that is more cost effective than current approaches and makes better use of available component health and cost data. These methods include both data- and model-based optimization methods. Model-based optimization methods directly include reliability and cost models to determine an optimal plant operational strategy. We consider gradient-based and evolutionary (based on genetic algorithms) optimization methods. The second class of methods target more specific use cases (e.g., project schedule optimization) and are not based on reliability models directly, but they require specific component reliability and cost data. This class of methods is based on variants of the knapsack problem with an aim to determine an optimal project schedule that maximizes the overall NPV. This paper also presents multi-objective methods designed to identify an optimal maintenance posture based on a Pareto frontier analysis. Rather than dictating the “right” tradeoff (i.e., identify the absolute best posture), we show how it is possible to perform a trade space exploration approach (i.e., identify value and costs of several postures and let the analysis account for desired value and cost metrics). This is performed by identifying maintenance postures that maximize value (e.g., system availability) and minimize operational costs, i.e., the Pareto frontier in a value-cost trade space. For all these methods we present detailed applicative examples that show their validity from a decision-making perspective.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Understanding Community Microgrids

Increasing need for distribution circuit reliability and resilience prompt a clearer understanding of community microgrid interconnection and operational requirements. While customer-owned, behind-the-meter microgrid implementation is not always simple, increasing demand for reliability has commercialized many installation approaches. This rapid commercialization has broadened industry understanding of single-customer microgrid integration. Moreover, off-grid behaviors of such microgrids are not required to meet utility standard interconnection requirements. However, multi-customer community microgrids (utility- or third-party operated), are less well explored and introduce more complex design and operational challenges. The control of DER along with distribution automation devices, unmanned operation, protection coordination, and other aspects makes community microgrids challenging to implement and operate in both on-grid and off-grid modes. This whitepaper is a technical primer for understanding community microgrids. It provides a foundation for understanding the components, configurations, design, and operational considerations for community microgrids.

14 SOLAR ENERGY↗
DOE OSTI2022

Demonstrating Advanced Nuclear Energy Solutions for Net Zero

Background/Objectives. The aggressive goals being set by nation states, communities, and private industry for decarbonization of grid electricity, industrial heat sources, and transportation around the world are imperative to mitigating the devastating effects that we are seeing from climate change. Although many of these goals focus on accomplishments by 2035 or 2050, the decisions that we make today won’t just impact the landscape of energy systems for the next 20 or 30 years—they will shape the world’s environment for centuries to come. That means that we can’t just focus on technologies that will get us to 2050, but technologies that will withstand our energy demands over that long-ranging future. Success will require us to utilize all of the clean energy resources that we have available to meet demands for electricity, heat, and steam, and we will need energy carriers such as hydrogen that do not emit additional greenhouse gases at the point of use. Nuclear energy, ranging from technologies in service today to advanced, higher temperature and modular systems that will be in service this decade, will provide a robust complement to renewable energy resources that operate variably. Researchers across the U.S. Department of Energy laboratory complex are working to advance multiple aspects of these clean energy solutions, with many focusing on integrated energy system solutions that leverage all available clean energy assets to meet wide-ranging energy demands. Approach/Activities. Nuclear energy is a proven, zero-emission option during operation that can provide consistent, dispatchable power to meet electricity demands while also providing high-quality heat that can meet energy demands beyond the electricity sector. Energy system design should seek to maximize these assets. As a dispatchable energy source with a small land utilization footprint, nuclear energy can be collocated with renewable resources, and the smaller systems that will be deployed this decade (ranging from a few megawatts to hundreds of megawatts) can be installed right where that energy is needed. Integrated nuclear and renewable systems will enhance power grid reliability and resilience, and they will help stabilize the grid through their increasingly flexible operation. Licensing, installation, and broad adoption of these advanced nuclear energy systems are expected to progress significantly in the 2020s, but this may be longer than desired by some stakeholders wishing to implement impactful clean energy decisions today. However, one must recall that nuclear energy systems will operate for 80 or more years, as is being demonstrated by current fleet nuclear systems. The nuclear community is extremely thorough in reviewing these systems with regard to safety and security; these efforts ensure that the deployed systems will continue to provide reliable, resilient energy over that operational lifetime. That investment of time up front will ensure that we can support energy demands over the centuries to come. While advanced nuclear technologies move through this process, communities and private industry may choose to install renewable generation systems that can later be coupled to the complementary nuclear systems as they become available—thus moving closer to the net zero goals in the near term. Choosing technologies and deployment configurations that allow small modular nuclear powerhouses to be added to these “energy parks” as they become available will ensure that advanced technologies can be readily adopted to support growing demands for clean energy. Results/Lessons Learned. The primary focus of integrated energy systems (IES) research is to assess the technical and economic potential of novel multi-input, multioutput solutions that are expected to enhance energy system flexibility, reliability, and resilience as we pursue a clean energy transition. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and various chemicals. In early FY23 Idaho National Laboratory (INL) will commission thermal energy generation systems that emulate nuclear fission energy input using electric heating and will allow for integrated system testing with thermal energy storage, hydrogen production via high temperature electrolysis (HTE), and power systems hardware to demonstrate operation of a clean energy park within a microgrid or larger grid infrastructure, supporting up to 450 kW of heat input via electric heating and demonstrating operation of HTE systems at the multi-hundred kW scale. This presentation will highlight the wide array of RD&D being conducted at INL and partner laboratories to develop and deploy nuclear and renewable-based IES that will be key to achieving our net zero goals, including both computational and experimental demonstrations. By working with key collaborators in industry, analytical st

08 HYDROGEN↗
DOE OSTI2023

Chapter 14 - Reliability of Wind Turbines

The global wind energy industry has grown at a fast pace during the past half-decade. Advancements from design and manufacturing to operation and maintenance have led to reduced capital and maintenance costs, which make wind power an indispensable source for a comprehensive solution to global electricity needs. Once wind turbines are installed, the opportunity to lower wind power costs is mainly through improved operation and maintenance practices. Modern wind turbines are equipped with tens or hundreds of measurement channels and are generating an abundance of data, with lot of efforts being put into data analysis by both the research community and the industry. One type of analysis is through the exploration of reliability engineering methods based on readily available data or maintenance records collected at typical wind power plants. If adopted and conducted appropriately, these analyses can quickly save operation and maintenance costs in a potentially impactful manner. The wind industry has adopted this discipline more broadly in recent years. This chapter discusses wind turbine reliability by highlighting the methodology of reliability engineering life data analysis. It first briefly discusses the fundamentals of wind turbine reliability and the current industry status. Then, the reliability engineering method for life analysis, including data collection, model development, and forecasting, is presented in detail and illustrated through two case studies. The chapter concludes with some remarks on potential opportunities to improve wind turbine reliability. An owner and operator's perspective is taken and mechanical components are used to exemplify the potential benefits of reliability engineering analysis to improve wind turbine reliability and availability.

database↗
DOE OSTI2023

Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Models Integrated in Instrumentation & Control Systems

In recent years, the field of machine learning (ML), specifically neural networks, has grown significantly and has spurred research in its applicability to digital instrumentation and control systems (DI&C). While ML models have shown promise in operational contexts, the trustworthiness of using such algorithms has not been adequately assessed. Failures of ML integrated systems are not well understood, and the lack of comprehensive risk modeling can degrade the trustworthiness in these systems. In recent reports by the National Institute for Standards and Technology (NIST) [1] and the Nuclear Regulatory Commission (NRC) [2], they indicate that trustworthiness in ML is a critical barrier and will play a vital role in the safe, accountable, and secure operation of intelligent systems. Thus, in this work, we demonstrate a dynamic model-agnostic method to quantify the relative reliability of AI/ML predictions by incorporating out-of-distribution (OOD) detection on the training dataset. It is well documented that most ML algorithms excel at interpolation (or near-interpolation) tasks but experience significant performance degradation at extrapolation. The method, referenced as the Laplacian distributed decay for reliability (LADDR), determines the difference between the operational and training datasets which can used to the relative reliability of AI/ML predictions. LADDR is then demonstrated on a feedforward neural network based digital twin used for the prediction of safety significant factors during a loss-of-flow transient. LADDR is used to demonstrate how training data can be used as evidence to support the relative reliability of ML/AI predictions enhancing the overall trustworthiness of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Accelerating Transitions to Zero Carbon Power Systems

As power systems evolve, becoming increasingly renewable, distributed, dynamic, and digital, managing them becomes ever more challenging and complex. System operators serve as the "air traffic controllers" for electricity grids, working to balance supply and demand, manage evolving electricity markets, and ensure the safety and reliability of electricity systems. To adapt to the rapidly changing energy landscape and support the transition to modern, zero carbon power systems, system operators must develop and adopt new technologies, approaches, and frameworks. The Global Power System Transformation (G-PST) Consortium is a network of system operators, research institutions, and industry partners working to accelerate and scale the technical solutions required to transform our world's power systems. By developing and sharing robust models and tools, research and demonstration results, knowledge, and innovation, the G-PST Consortium is empowering system operators to transition to 100% renewable energy while ensuring the reliability, safety, and cost-effectiveness of grid operations.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2022

Design and Implementation of Automated Characterization of T-type based Power Module for PV Inverter Reliability Assessment

Reliability of power electronics holds the key for future power and energy systems since it is essential for system integration with renewables and energy storage systems. Variation of power module characteristics over the converter’s operational lifetime is a critical indicator to assess its reliability. Device characterization consists of different steps to collect, process, and visualize results, which is usually time-consuming, especially for power modules based on a non-phase-leg configuration, such as T-type circuits, widely applied for PV inverters. To reduce the time, ensure repeatability, and guarantee consistency, an automated test bench can be helpful. This paper focuses on a T-type-based power module and proposes a unique characterization platform and corresponding automation procedure and implementation. Considering the major characterization difference between T-type power modules over the conventional phase-leg power module, first, the special consideration for static characterization is highlighted. Second, the unique dynamic characterization design associated with the T-type power module is described. Finally, the automation of the power module characterization and the test platform is presented along with results and special considerations.

Siraj, Ahmed↗
DOE OSTI2025

Toward the first gluon parton distribution from the LaMET

Abstract We present progress towards the first unpolarized gluon quasi-parton distribution function (PDF) from lattice quantum chromodynamics using high-statistics measurements for hadrons at two valence pion masses M π ≈ 310 and 690 MeV computed on an a ≈ 0.12 fm ensemble with 2 + 1 + 1-flavors of highly improved staggered quark generated by the MILC collaboration. In this study, we consider two gluon operators for which the hybrid-ratio renormalization matching kernels have been recently derived and a third operator that has been used in prior pseudo-PDF studies of the gluon PDFs. We compare the matrix elements for each operator for both the nucleon and pion, at both pion masses, and using two gauge-smearing techniques. Focusing on the more phenomenologically studied nucleon gluon PDF, we compare the ratio and hybrid-ratio renormalized matrix elements at both pion masses and both smearings to those reconstructed from the nucleon gluon PDF from the CT18 global analysis. We identify the best choice of operator to study the gluon PDF and present the first gluon quasi-PDF under some caveats. Additionally, we explore the recent idea of Coulomb gauge fixing to improve signal at large Wilson-line displacement and find it could be a major help in improving the signal in the gluon matrix elements. This work helps identify the best operator for studying the gluon quasi-PDF, shows higher hadron boost momentum is needed to implement hybrid-ratio renormalization reliably, and suggests the need to study more diverse set of operators with their corresponding perturbative calculations for hybrid-ratio renormalization to further gluon quasi-PDF study.

Good, William (ORCID:0000000184281003)↗
DOE OSTI2021

VSC-HVDC Interties for Urban Power Grid Enhancement

Urban power grids are facing many operational and expansion challenges to meet further demand growth and increased reliability requirements. Advanced transmission technologies have been considered by the electric utilities to effectively increase the utilization of existing infrastructure and operational flexibility. The focus of this paper is on VSC-HVDC technologies for urban power grid enhancement and modernization. First, a potential technical scheme is proposed for converting an existing AC circuit to DC operation, which could boost the power transfer capability of the critical transmission corridor and increase network operational flexibility. Second, this paper proposes three operation modes for the VSC-HVDC interties in urban power grids corresponding to normal, emergency and island operating conditions, respectively. An integrated, adaptive emergency control strategy (AEC) is proposed that can enable adaptive power flow responses of the VSC-HVDC intertie under varying system operating conditions and critical contingencies. The flexibility and effectiveness of the proposed operational principles of urban VSC-HVDC intertie and the corresponding control strategies are verified in PSCAD/EMTDC using a realistic urban power grid in China.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Sub-THz passive detector performance evaluation with RadiaBeam photoinjector

Wakefield accelerators, based on THz and mm-wave structures, promise to reach the highest energies in record small footprints. However, operation at such frequencies is associated with strong generation of dipole modes that can destroy the beams, which requires controlling the electron beam position at the micron scale. The existing conventional techniques for electron beam position monitoring are not applicable for sub-THz structures due to the space constraints. Here, on the other hand, if dipole modes amplitudes can be measured precisely at different planes, one can derive beam position relative to the central axis. For such a technique a reliable and cost-effective sensor capable of operating in high repletion rate regime is required. In this paper we review the experimental evaluation of a passive sensor candidate for such applications using RadiaBeam 4.5 MeV photoinjector.

Accelerator↗
DOE OSTI2024

Fully Scalable Randomized Benchmarking Without Motion Reversal

We introduce , a protocol that streamlines traditional RB by using circuits consisting almost entirely of independent identically distributed (IID) layers of gates. BiRB reliably and efficiently extracts the average error rate of a Clifford gate set by sending tensor-product eigenstates of random Pauli operators through random circuits with IID layers. Unlike existing RB methods, BiRB does not use motion reversal circuits—i.e., circuits that implement the identity (or a Pauli) operator—which simplifies both the method and the theory proving its reliability. Furthermore, this simplicity enables scaling BiRB to many more qubits than the most widely used RB methods. Published by the American Physical Society 2024

Hines, Jordan (ORCID:0000000151267256)↗
DOE OSTI2020

Development and Test of High Temperature Surface Acoustic Wave Gas Sensors

The demand for sensors in hostile environments, such as power plant environments, aerospace environments, oil and gas extraction, and high-temperature metallurgy environments, has risen over the past decades in a continuous attempt to increase process control, improve energy and process efficiency in production, reduce operational and maintenance costs, increase safety, and perform condition-based maintenance in equipment and structures operating in high-temperature harsh-environment conditions. The increased reliability, improved performance, and development of new sensors and networks with a multitude of components, especially wireless networks, are the target for operation in harsh environments. Gas sensors, in particular H2 sensors, operating above 200 C are required in the instrumentation, process control and general safety of a number of industries including coal, natural gas, and nuclear power generation facilities, the aerospace and automotive industries, metallurgical production and defense-related applications. The surface acoustic wave (SAW) platform is a particularly promising option for high-temperature, harsh-environment gas sensing applications since the platform exhibits advantages, such as battery-free and wireless operation, small size, possibility for scale production using well-developed technologies from the semiconductor industry, and low cost of installation and operation. In this work, one-port SAW resonators (SAWRs) operating along five different orientations on a commercially available langasite (LGS) wafer employing Pt-Al2O3 electrodes and reflectors were designed, fabricated, and used as high-temperature H2 sensors. Two of the selected orientations were predicted and confirmed to have temperature-compensated operation above 150 C. A gas sensor test setup was developed, capable of gas cycling between N2, O2 and N2/H2 mixtures under extended high-temperature periods (up to 650 C for over 20 hours). Thin film Pt-Al2O3 was used as the electrode material for the transducers and reflectors capable of high-temperature operation, and also as H2 sensing film. In addition, yttria-stabilized zirconia (YSZ) thin films with Pt decoration were tested as sensing films aimed to enhance the SAWR sensor response to H2. The SAW devices were monitored in excess of 1700 hours in real-time during gas cycling sequences up to 600 C, leading to the following findings: i) the Pt-Al2O3 electrodes performed better for H2 sensing than the Pt-decorated YSZ sensing film, showing as much as 50% higher frequency variation response in the 200 C to 400 C range; ii) different crystallographic orientations operating on the same LGS wafer experienced different responses to H2 exposures up to 500 C; iii) the surface oxidation state of the SAWR sensors was shown to have an important impact on subsequent H2 exposure responses. In addition, a sensor system employing two LGS SAWRs, aligned along two different orientations, has been developed to simultaneously determine H2 presence and temperature. Finally, wireless interrogation of a SAWR sensor was successful within the gas cycling test fixture, and successful wireless H2 detection was achieved above 400 C.

Ayes Moncada, Armando↗