Search NASA⌕ Search

SEARCH · Search NASA

Results for “Casting Operations”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development of Cast Valve Bodies For High Temperature Service

Gen 3 Concentrating Solar-Thermal Power (CSP) system components are required to operate at 750°C - 800°C to achieve the Sunshot target of 6 cents/kWh. Haynes ® 282 and IN ® 740H are preferred alloys for the construction of these components due to their high tensile and creep strengths for service at temperatures greater than 750°C. There is significant motivation to lower the cost of materials and components so that the capital costs can be minimized. One approach to reduce costs is to fabricate castings at the lowest possible cost. To obtain the lowest cost in castings, there is a significant need to maximize yields in castings by decreasing rejects due to casting defects and to minimize wastage in material lost in the gating systems. However, very little work has been performed to develop cast products using Haynes ® 282. Although preliminary work has established the feasibility of casting Haynes ® 282 using investment and sand casting, there are no commercial cast components available. In particular, there is significant interest in the development of casting design and process technology for the fabrication of components such as valve bodies using Haynes ® 282.

14 SOLAR ENERGY↗
DOE OSTI2021

Precipitate Phase Stability and Mechanical Properties of Alloy 263 and Variants in Wrought or Cast Form

Alloy 263 is a candidate Ni-based superalloy for use in advanced ultra-supercritical (AUSC) power plants that are targeted to operate above 700 °C. Exposure times in this type of environment are considerable with target creep properties specified at 100,000 h making phase stability an important parameter in the alloy selection process. In this investigation, the microstructure of alloy 263 and two modified compositions in both cast and cast/wrought forms were investigated after exposure at 800 °C for various times ranging from 1,000 h to 10,000 h. Tension and creep properties were assessed for all alloys in both forms. Modification to the Ti and Al concentrations successfully slowed down the γ' to η transformation while doubling the γ' fraction. Thin elongated η needles or platelets formed in the wrought products while thicker, plate-like, η precipitates were found in the castings. The effect of the various microstructures on the creep properties were determined using isothermally aged specimens aged at 800 °C for 3,000 h and 10,000 h prior to creep screening. Strong precipitation of the η phase was found to considerably decrease creep life and increase minimum creep rate. By modifying the Ti and Al content, the creep life and ductility of the new formulation tested on specimens isothermally aged for 3,000 and 10,000 h were near that of the nominal alloy in its standard aged condition.

Detrois, Martin↗
DOE OSTI2024

Measuring thermal profiles in high explosives using neural networks

We present a new method for calculating the temperature profile of high explosive (HE) material using a Convolutional Neural Network (CNN). To train/test the CNN, we have developed a hybrid experiment/simulation method for collecting acoustic and temperature data. We experimentally heat cylindrical containers of HE material until detonation/deflagration, where we continuously measure the acoustic bursts through the HE using multiple acoustic transducers lined around the exterior container circumference. However, measuring the temperature profile in the HE in an experiment would require inserting a large number of thermal probes, which would disrupt the heating process. Thus, we use two thermal probes, one at the HE center and one at the wall. We then use numerical simulation of the heating process to calculate the temperature distribution and correct the simulated temperatures based on the experimental center and wall temperatures. We calculate temperature errors on the order of 15 °C, which is ∼12% of the range of temperatures in the experiment. We also investigate how the algorithm’s accuracy is affected by the number of acoustic receivers used to collect each measurement and the resolution of the temperature prediction. This work provides a means of assessing the safety status of HE material, which cannot be achieved using existing temperature measurement methods. In addition, it has implications for a range of other applications where internal temperature profile measurements would provide critical information. These applications include detecting chemical reactions, observing thermodynamic processes such as combustion, monitoring metal or plastic casting, determining the energy density in thermal storage capsules, and identifying abnormal battery operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Measuring thermal profiles in high explosives using neural networks

We present a new method for calculating the temperature profile of high explosive (HE) material using a Convolutional Neural Network (CNN). To train/test the CNN, we have developed a hybrid experiment/simulation method for collecting acoustic and temperature data. We experimentally heat cylindrical containers of HE material until detonation/deflagration, where we continuously measure the acoustic bursts through the HE using multiple acoustic transducers lined around the exterior container circumference. However, measuring the temperature profile in the HE in an experiment would require inserting a large number of thermal probes, which would disrupt the heating process. Thus, we use two thermal probes, one at the HE center and one at the wall. We then use numerical simulation of the heating process to calculate the temperature distribution and correct the simulated temperatures based on the experimental center and wall temperatures. We calculate temperature errors on the order of 15 °C, which is ~12% of the range of temperatures in the experiment. We also investigate how the algorithm’s accuracy is affected by the number of acoustic receivers used to collect each measurement and the resolution of the temperature prediction. This work provides a means of assessing the safety status of HE material, which cannot be achieved using existing temperature measurement methods. In addition, it has implications for a range of other applications where internal temperature profile measurements would provide critical information. These applications include detecting chemical reactions, observing thermodynamic processes such as combustion, monitoring metal or plastic casting, determining the energy density in thermal storage capsules, and identifying abnormal battery operations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Methods of sheet metal production and sheet metal products produced thereby

Processes for producing sheet metal products by machining a solid metal body with a cutting tool in a single step to continuously produce a continuous bulk form from material obtained from the solid metal body, and without performing a hot rolling operation thereon, cold rolling the continuous bulk form to produce a sheet metal product. The machining step is a large-strain machining process capable of being directly performed on an as-cast ingot or other solid body to produce a continuous intermediate product that can be directly cold rolled without any intervening hot rolling operation, and optionally without homogenization or annealing.

Trumble, Kevin Paul↗
DOE OSTI2023

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

High Throughput Solvent-free Manufacturing of Battery Electrodes

The project goal is to develop and demonstrate an advanced solvent-free lithium-ion battery electrode process through proposed Advanced Dry Electrode Process (ADEP) equipment, which is expected to exhibit a better binder fibrillization and high throughput and suitable for high performance electrode manufacturing, and commonize the anode and cathode dry processing equipment, supply chain and operation for lithium-ion battery OEMs for replacing the solvent-based slurry casting. Our proposed approach will facilitate low-cost battery production by addressing the following gaps in present dry electrode processing: • Extend the dry electrode fabrication process to lithium-ion battery anode manufacturing • Increase the active material content for anodes and cathodes • Intensify the process through improved mixing, powder rheology and surface modifications • Enable processing of next-generation electrode materials that are not stable to solvent or ambient air exposure. The project objectives include the development of anode-compatible binder and binder fibrillization promoter for low irreversible capacity loss, low electrode binder content yet higher film mechanical strength, and the optimization of solvent-free anode and cathode process for low cost (>60% electrode cost reduction), high performance (10% increase in energy density without sacrificing cycle life) and high throughput to enable next generation lithium-ion battery electrode production. Solvent-free electrode manufacturing will also enable next-generation cell designs based on prelithiated anodes or solid-state electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2020

Study of Additive Manufacturing Application to Geothermal Technologies

Geothermal reservoir characterization, field construction, and reservoir operations are very technology intensive activities that contribute significantly to the cost of delivering electricity produced from geothermal resources. Many geothermal technologies, such as downhole tools and drilling equipment, have unusual material, design, and manufacturing considerations dictated by the harsh geothermal environment and extreme aspect ratios required for deployment in a borehole. An additional challenge that faces geothermal applications is the low tool production volume needed to support the industry. Whereas tens of thousands of Oil & Gas wells are drilled and completed in the U.S. annually, there are typically only tens of geothermal wells that are drilled and completed. If a tool typically used in Oil & Gas applications cannot be directly used for geothermal, then the cost associated with making the tool suitable for geothermal is often prohibitive. There is therefore a much smaller inventory of technologies available to geothermal as compared to Oil & Gas and the level of efficiency and sophistication associated with field practice suffers accordingly. A number of advanced manufacturing methods, such as additive manufacturing, have received increased R&D as well as commercial attention in recent years because of their ability to rapidly prototype complex parts. Additive manufacturing in particular provides an opportunity to increase the technology available to the geothermal industry by either reducing fabrication costs associated with complex components or enabling economic production of low volume parts where specialized tooling is often required. Additional potential benefits of additive manufacturing include increased design freedom to make higher performing parts that cannot be made conventionally, the ability to integrate components into assemblies without joining operations, and the ability to economically fabricate variations on design in cases, such as casting molds, where there are large up-front costs associated with tooling. We have recently completed a study that investigated technology needs, representative use cases, manufacturability, and a techno-economic framework for comparing conventional to additive manufacturing methods for geothermal applications. This paper will provide an overview of this recent effort, describe the different elements of the assessment, and summarize the key takeaways related to both the feasibility of using additive manufacturing for geothermal technology applications as well as the potential benefits and impacts.

Polsky, Yarom↗
DOE OSTI2020

Monte Carlo simulations of Cu/Ni–Si–Mn co-precipitation in duplex stainless steels

First-Passage Kinetic Monte Carlo (FPKMC) simulations of species migration in duplex stainless steels were performed in order to establish relationships between alloy content, segregation behavior, and the formation of Ni-Si-Mn rich particles in cast duplex stainless steels during thermal aging. The Ni-Si-Mn-rich second phase forms after extended aging at reactor operating temperatures and degrades alloy properties. Simulations of Ni-Si-Mn cluster formation were validated through comparison with experimental results obtained through Atom Probe Tomography (APT) on similar alloy compositions, identifying several trends. First, Cu promotes the formation of Ni-Si-Mn clusters, but only when Ni or Mn prefer segregation to the surface of Cu particles; without the segregation of these species, the critical composition for the clusters to form was not achieved. Second, the width of precipitate-denuded zones near ?/d interfaces increases with decreasing Cu content. This finding was in strong agreement with APT results, further validating our model. Finally, our model predicts that Ni-Si-Mn cluster formation will be the most extensive when the Si:Mn ratio is approximately 1:1 and the least extensive when one of these key elements is less concentrated (Mn = 0.5 at.% or Si = 0.5 at.%). The implications of these results on how to improve alloy properties are discussed.

Cu co-precipitation, Atom probe tomography (APT), ↗
DOE OSTI2020

Thermomagnetic Processing of Aluminum Alloys During Heat Treatment

Processing materials under magnetic fields is an underexplored technique to improve structure and mechanical properties in metals and alloys. Magnetic fields can alter phase stability, modify diffusion characteristics, and alter material flow substantially. In castings, magnetic fields can be used during melting of the alloy, during solidification, or during postprocessing operations such as heat treatment to achieve structural changes. This work investigates the effectiveness of thermomagnetic processing during heat treatment of Al alloys containing in the Al–Cu, Al–Si–Cu, and Al–Mg–Ce systems. We demonstrate an improvement in mechanical properties and a reduction in required heat treatment times for all alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Simple, Scalable Large Deformation Solid Mechanics Implementation in the MOOSE Framework

This article describes a large deformation solid mechanics solver implemented as part of the freely available and open source MOOSE finite element simulation framework. The article documents the choices made in developing the solid mechanics framework and describes novel formulations for the gradient operator and constitutive modeling framework made to simplify implementations of different coordinate systems, stabilized gradient operators, and different constitutive model inputs and outputs. In the process, the article describes a new formulation that casts objective integration of the Cauchy stress as a linear transformation of the small stress rate. Finally, the article presents key implementation details and examines the parallel efficiency of the solid mechanics solver implemented in MOOSE. The implementation retains a good weak scaling efficiency beyond 1,000 parallel processes. The article includes a discussion of the factors limiting the parallel efficiency of implicit, large deformation solid mechanics codes on current high-performance computers, with the main current limitation being the scalability of the algebraic multigrid methods used to solve the linearized equilibrium equations.

Applied computing → Computer-aided design↗
DOE OSTI2025

Evaluation of Pozzolan-substituted Cast Stone for Pretreated Hanford Tank Waste

Portland cement. The future availability of quality Class F fly ash has come into question as coal-fired power plants are being converted to gas or taken offline. Consequently, alternative pozzolanic reagents are being evaluated for fly ash replacement in cementitious matrices for treating radioactive waste and debris. In 2023 and 2024, Savannah River National Laboratory (SRNL) was funded to evaluate natural pozzolans for the replacement of Class F fly in the Savannah River Site (SRS) Saltstone formulation. Based on the promising results and uncertain availability of Class F fly ash in the northwestern US, Hanford Tank Waste Operations & Closure, LLC (H2C) requested SRNL to evaluate the potential for substituting natural pozzolans in the Hanford West Area Pretreated Low Activity Tank Waste (PTW/LAW) Cast Stone formulation1 . Task 1 in this request was to determine the change in Cast Stone volume resulting from stabilization/solidification of 1 L of PTW/LAW tank waste. The densities of three (Hess Pumice, tephra pumice, and clinoptilolite zeolite) pozzolan-substituted Baseline Cast Stone mixes were determined, and volume changes relative to the fly ash-Baseline Mix with a water-to-dry mix = 0.40 were calculated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Additive Manufacturing Case Study

Geothermal technologies include an extremely wide range of products required for well construction, completion, production, intervention and surface energy conversion activities. Many of these products are geometrically complex, require multi-step and highly specialized fabrication processes, and are expensive due to the low production numbers typically associated with the geothermal market. These challenges along with the high temperature demands of the geothermal environment have also hindered the adoption of many tools routinely used in the oil & gas industry.Recent advancements in Additive Manufacturing (AM) materials of construction, build volumes and part quality have transitioned the technology from primarily cosmetic prototyping applications to the point where AM can be used to make production parts, even for the most demanding applications. These improved AM capabilities along with the inherent ability of AM to produce complex parts and, in some cases, geometries that cannot be manufactured using conventional casting, machining and joining fabrication approaches motivate an exploration of its potential to positively impact geothermal well construction and operations technologies.Sandia National Labs collaborated with Oak Ridge National Laboratory on a case study examining additive manufacturing opportunities for Geothermal applications. The study focused on designing components with improved performance characteristics that cannot be fabricated conventionally. A rotor for a downhole motor was chosen based on the potential for improving its rotational dynamics. Topology optimization was used as a design method to reduce the rotational inertia of the part while preserving sufficient rotational stiffness to transmit the torque required for the drilling application. The optimization resulted in a nearly 50% reduction in polar moment of inertia while maintaining other desired performance characteristics. The design developed using the topology optimization approach was fabricated using additive manufacturing and cannot be fabricated conventionally. This paper will discuss the design approach, performance improvements and manufacturing methods used to produce the part.

Polsky, Yarom↗
DOE OSTI2020

Rapid Retooling for Emergency Response with Hybrid Manufacturing

The global manufacturing industry has served as a keystone in supporting the weight of emergency response operations during the coronavirus disease (COVID-19) pandemic. Development of core technologies necessary to prevent the spread of COVID-19, including Personal Protective Equipment, infection testing kits, and vaccine research supplies, requires intensive manufacturing operations to support a population at scale. The production of these items is traditionally dependent on the tool and die industry, requiring imports of steel castings from overseas suppliers. The United States (U.S.) manufacturing industry was left isolated and unprepared as international borders closed overnight and normal supply chains were cut. This technical note provides a forward-looking approach at the benefits of hybrid manufacturing processes to provide rapid reconfiguration capabilities in the U.S. tool and die industry. A demonstration in rapid production of new tooling is provided to illustrate these benefits. Finally, emerging hybrid technologies are discussed in pursuit of more flexible manufacturing operations.

42 ENGINEERING↗
DOE OSTI2020

Degradation of impact toughness in cast stainless steels during long-term thermal aging

Cast austenitic stainless steels (CASSs) have been extensively used for the large components of nuclear reactor primary coolant systems. Since the cast steels inevitably contain degradable metastable phases and replacement of the large coolant system components is impractical, the thermal embrittlement of CASS components has been a serious concern in the extended-term operation of nuclear power plants. This study aimed to systematically measure and analyze the effect of long-term thermal aging on the Charpy impact toughness to provide a comprehensive understanding of thermal degradation behavior and a practical aging model to predict the degree of thermal degradation in the cast stainless steels. Additionally, the materials tested in the research include eight CASS alloys (two CF3s, one CF3M, three CF8s, and two CF8Ms) and two reference wrought materials (304L and 316L), in which the nominal δ-ferrite content ranges from ~2% to 33%. These stainless steels have been thermally aged at two light water reactor (LWR) temperatures (290 and 330 °C) and at two accelerated-aging temperatures (360 and 400 °C) for up to 30,000 h; these include both under-aged and over-aged conditions relative to the extended service lifetime (80 years). Charpy impact testing was performed for aged and non-aged specimens, and the impact (absorbed) energy parameters were correlated with a new aging parameter (A). Both the reduction of impact fracture toughness and the shift of ductile-brittle transition temperature were strongly dependent on the δ-ferrite content and degree of thermal aging. A linear relationship was found between the increasing rate of the index transition temperature T 41J and aging parameter A; base on which an empirical model was proposed for prediction of the transition temperature as a simple function of the aging parameter (A) and δ-ferrite content (F). Finally, the critical aging parameter for embrittlement (AC) was evaluated and compared with the existing δ-ferrite content criteria.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗
DOE OSTI2022

Improved Creep and Tensile Properties of a Corrosion Resistant Ni-Based Superalloy Using High Temperature Aging and Nb/Ta Additions

Resistance to creep deformation is essential for cast and wrought Ni-based superalloys in next generation energy systems due to the considerable exposure times required at the operating temperature. Here the amount of precipitate strengthening was increased in variants to Inconel alloy 725 (IN725), a corrosion resistant alloy, to improve its elevated temperature mechanical strength. Additions of Nb or Ta coupled with a high temperature aging (HTA) heat treatment promoted the formation of γ" precipitates and grain boundary phases which led to significant increases in time to failure. The HTA increased the creep life of various alloy formulations as compared to the standard aging heat treatment with a maximum improvement of 371%. The Nb and Ta additions lowered the minimum creep rate (MCR) and had a similar effect on increasing creep life. The positive effect of the additions was more pronounced when coupled with the HTA which employed a higher temperature in the first step of the heat treatment to promote precipitate phase formation. The Ti/Al ratio was used to design alloys with preferential formation of ' or γ" precipitates. Compact morphology precipitates were formed in the alloys with a low Ti/Al ratio. While a low Ti/Al ratio was primarily associated with lower MCRs, the effect on the creep life was less evident than that of the HTA. By using additions of Nb or Ta and a HTA heat treatment, the creep life of IN725 for testing at 973 K (700 °C) and 483 MPa was improved by up to 256%.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Creep-Resistant Ferritic-Martensitic Steels for Power Plant Applications

Creep-resistant ferritic-martensitic steels are essential materials used in power plants for electricity generation. The efficiency and emissions of the plant are closely related to the operating temperature. Materials used in the hottest sections are one of the main limiting factor for plant operation at 650 °C. This review describes the recent development of creep-resistant ferritic-martensitic steels from a large dataset of in-house research. The findings are tied to available literature for discussion. A first steel, CPJ-7, was developed with an operating temperature approaching 650 °C, and a refined design, JMP, showed the potential to operate at 650 °C. Approximately fifty different ingots, each weighing ~ 7 kg, were vacuum induction melted and processed. Overall, wrought and cast versions of CPJ-7 present superior creep properties when compared to wrought and cast versions of COST alloys for steam turbine and P91/92 for boiler applications. The prolonged creep life was attributed to slowing down the process of the destabilization of the MX and M 23 C 6 precipitates at 650 °C. The cast version of CPJ-7 also revealed superior mechanical performance, above commercially available cast 9% Cr martensitic steel or derivatives. Following the work on CPJ-7, the JMP steels were designed with higher Co for increased solid solution strengthening, Si for oxidation resistance and increased W for matrix strength and stability. The JMP steels showed increases in creep life compared to CPJ-7 between 118 and 150% at 650 °C for testing at various stresses between 138 and 207 MPa. On a Larson–Miller plot, the performance of the JMP steels surpasses that of state-of-the-art MARBN steel. The influence of various elements within the composition of the alloys on the microstructure and mechanical properties is discussed. This review presents approximately 420,000 h of in-house creep testing, the equivalent of almost 50 years of cumulative creep tests.

36 MATERIALS SCIENCE↗