Recombination and Resistive Losses of Transferred Foil Contacts for Silicon Heterojunction Solar Cells
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Materials Science↗
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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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Vehicle-to-manufacturing (V2M) system: A novel approach to improve energy demand flexibility for demand response towards sustainable manufacturing
The U.S. manufacturing sector accounts for 77% of the industrial energy consumption, but its participation in demand response (DR) programs is largely lagged behind. The limited flexibility in production scheduling under high capacity utilization and the lack of DR schemes that incorporate energy demand flexibility measures are deemed as major barriers. In this study, a framework of the interactive vehicles-to-manufacturing (V2M) energy sharing system is proposed to improve the energy demand flexibility of the aggregated system and enhance the DR effectiveness for manufacturers. The V2M-based DR scheme aims to reduce the energy cost by load shifting through joint production and energy sharing control, which can eventually promote manufacturing DR implementation even under high capacity utilization requirements and dynamic real-time electricity prices. The V2M system is modeled based on a discrete-Markov chain considering the complex interconnections among various manufacturing resources and multi-directional energy flows among manufacturing facilities, electric vehicles, and the power grid. Based on the system model, a mixed-integer nonlinear programming (MINLP) problem is formulated to identify the optimal DR scheme. The effectiveness of the proposed approach is validated through comparisons with traditional manufacturing DR schemes. Finally, the results show that a 2.1 to 6.5 times energy demand flexibility improvement and an additional 4.7% to 6.9% energy cost reduction can be achieved by the proposed approach.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Framework for optimization of long-term, multi-period investment planning of integrated urban energy systems
In order to achieve stringent greenhouse gas emission reductions, a transition of our entire energy system from fossil to renewable resources needs to be designed. Such an energy transition brings two main challenges: most renewables generate variable electric energy, yet most demand is currently not electric (carrier mismatch) and does not always manifest at the same time as supply (temporal mismatch). Integrating multiple energy infrastructures can address both challenges by using the synergy between different energy carriers; building on existing infrastructure, while allowing a robust and flexible integration of the new. This paper proposes an optimization framework for long-term, multi-period investment planning of urban energy systems in an integrated manner. We formulate it as a mixed-integer linear program, combining a capacitated facility location with a multi-dimensional, capacitated network design problem. It includes generation and network expansion planning as well as interconnections between networks and storage infrastructure for each energy system. It can incorporate pathway effects like techno-economic developments, policy measures, and weather variations. The intended use is to support urban decision makers with long-term investment planning, though it can be tailored to fit other geographical or temporal scales. We demonstrate the model using two cases based on an average city in The Netherlands, which wants to reduce its CO 2 -emissions with 95% by 2050. In the first case, we include explicit carbon-emission constraints to study the effects of the carrier mismatch. In the second case, we implement interannual weather variations to analyze the temporal mismatch. The results give valuable insights into the energy transition design strategy for urban decision makers. They also show the future potential, as well as the computational challenges of the optimization framework.
24 POWER TRANSMISSION AND DISTRIBUTION↗
The ATTO-Campina site: A new observatory for tropical convection and gas-aerosol-cloud-precipitation interactions in the Amazon
We present results from ATTO-Campina, a new permanent observational site in central Amazon, about 4 km from the ATTO towers. Operational since 2020, ATTO-Campina characterizes atmospheric, cloud and rainfall properties through remote sensing. The goal is to provide continuous, complementary measurements to the ATTO towers, addressing the rainforest’s complex gas-aerosol-cloud-precipitation dynamics. Using a 3.5-year dataset, we classified convective clouds into three types: shallow cumulus (ShCu), congestus (Con) or (Deep) clouds. The shallow-to-deep transition takes about three hours, starting with ShCu formation at 11:00 local time. The accumulated rainfall peak follows at about 16:00. Only weak downdrafts are present in the upper troposphere where previous studies indicate new particle formation (NPF) occurrence. Strong downdrafts are mostly limited to heights below 5 km. Con and Deep convective days have higher concentrations of ultrafine aerosol and lower concentrations of accumulation-mode particles compared to ShCu. Convective clouds also significantly modify gas mixing ratios. Deep convective clouds are associated with high near-surface O3, consistent with downward transport from the midtroposphere. Our results showcase the added detail achieved by integrating data from the ATTO towers and ATTO-Campina sites. Together, these sites support better understanding of interconnected gas-aerosol-cloud-precipitation processes in the Amazon and their evolution under climate change.
54 ENVIRONMENTAL SCIENCES↗
Slow Wake Recovery and Low Turbulence Behind Wind Farms Parameterized in Mesoscale Simulations
Numerical weather prediction (NWP) and climate models equipped with wind-farm parameterizations (WFPs) can simulate cluster wake effects affecting downstream wind farms in both onshore and offshore environments. This study evaluates wake recovery behind a wind farm represented by the NWP-WFP approach in the Weather Research and Forecasting (WRF) model using either the Fitch et al. (2012) or Ma et al. (2022a, b) WFPs. Results are benchmarked against large-eddy simulations (LES) of an idealized offshore wind farm with aligned and staggered layouts under neutral atmospheric stability. Near-farm wake recovery is underestimated in NWP-WFP simulations due to its representation on a coarse mesoscale grid. This limitation leads to slow wake recovery through two interconnected mechanisms: (i) spatial gradients in the wind velocity field are weaker compared to LES and (ii) turbulence kinetic energy (TKE) remains low not because of excessive dissipation but due to insufficient shear production caused by these weakened gradients. For the scenario considered here, a wind-speed bias develops in the near-farm wake and persists into the far wake. Differences between the NWP-WFP simulations and LES emerge within a short distance downstream of the farm exit, where the mesoscale simulations recover too slowly. This reduced recovery contributes approximately 0.15-0.50 m s-1 to the near-farm wind-speed bias. The bias established in this region is not subsequently compensated for downstream but instead propagates into the far wake, where wind-speed differences of approximately 0.4-0.6 m s-1 remain up to 50 km downstream. Higher-resolution mesoscale simulations partially reduce this bias. Increasing turbine-added TKE or including subgrid wake effects provides additional improvement, but neither fully addresses the underlying cause. The slow wake recovery is not caused by limitations of the WFPs themselves, as it also occurs outside their region of influence, and adding subgrid wake effects does not significantly impact recovery. Rather, the slow wake recovery is a consequence of mesoscale flow representation. This behavior is not limited to regions downstream of the wind farm but is less visible within the farm, where wake recovery occurs simultaneously with turbine-induced momentum extraction. These results highlight the need for improved representations of wake recovery both within and downstream of wind farms. While enhanced subgrid modeling, shear-driven TKE production, and refined WFP formulations may improve intra-farm dynamics, accurately capturing near-farm wake recovery downstream remains challenging, as WFPs do not act in this region.
17 WIND ENERGY↗
Attack-resilient algorithms and testbed federation for wide-area protection and control in smart grid
Today’s energy infrastructure is undergoing a massive transformation across all generation, transmission, and distribution systems to provide reliability, efficiency, and sustainability to the power system network. During the past 10 years, there has been a remarkable enhancement in developing close-loop wide-area protection and control (WAPAC) applications, such as automatic generation control (AGC), wide-area protection scheme (WAPS), synchrophasor-based wide-area voltage control system (WAVCS), etc., in the energy management system (EMS) to provide an adequate situational awareness to control center operators during physical disturbances and natural events. The rapid digitalization, unencrypted communication, and numerous data-sharing devices have increased digital access points that have exposed the grid network to countless cyberattacks pertinent to the WAPAC cybersecurity. Given the amount of complex grid network coupled with legacy infrastructures, it is untrustworthy to completely rely on information technology (IT)-based conventional security measures to defend against evolving cyberattacks. Hence, there is a compelling need to go beyond the traditional paradigm of ‘security by obscurity’ and ‘bolt-on’ security measures, and develop a suite of innovative security solutions at multiple layers to transform the current “fault-resilient” grid into “fault and attack-resilient” grid of the future. This dissertation specifically focuses on developing application-specific attack-resilient solutions for critical WAPAC applications in the smart grid. The first part of the study, Attack-Resilient Wide-Area Protection Scheme, presents a cyber-physical attack-resilient system (CPARS) for WAPS, where two anomaly detection methods are proposed to detect multi-level cyberattacks followed by the rules-based intrusion mitigation system (RIMS) to initiate effective mitigation strategies, tailored to these attacks, to restore the normal grid operation after disturbances. The first anomaly detection component, Machine learning-based Anomaly Detection for Centralized WAPS, discusses a novel architecture and methodology for developing a machine-learning-based anomaly detection system (ADS) for the centralized wide-area protection system (CWAPS) by applying the variational mode decomposition (VMD) technique and decision tree (DT) algorithms using cyber logs and synchrophasor measurements. The second component, Multi-Agent-based Anomaly Detection for Decentralized WAPS, presents a two-level hierarchical multi-agent-based decentralized WAPS against the system-aware stealthy cyber-attacks. Finally, for the RIMS, the state transition diagram-based mitigation measures are defined based on the grid operation states and experimental testing and evaluation are presented in a cyber-physical testbed environment. The second part of the study, Attack-Resilient Wide-Area Voltage Control System, addresses the existing vulnerabilities in the wide-area voltage control system (WAVCS), presents the methodology for performing an impact analysis during data integrity attacks, and proposes a data-driven attackresilient system (DARS) by incorporating machine learning-based ADS and rules-based anomaly mitigation system (RAMS) to detect these attacks and provide necessary mitigation actions to maintain the transient voltage stability after disturbances. Finally, the third part, Networked Federation Testbed (NEFTSec) for Smart Grid Cybersecurity, focuses on developing an interconnected federated testbed through a common network like the internet, describes its conceptual architectures, and also presents its design components for experimental testing, validation, and evaluation. Further, it presents the co-simulation interface algorithm (CIA) to facilitate the geographically-dispersed real-time distributed simulation (GD-RTDS) during the cyber-physical federation. In general, this dissertation presents innovative attack-resilient solutions for WAPAC applications that are experimentally tested and evaluated using the PowerCyber testbed and NEFTSec platform to accelerate the transition of state-of-the-art research works to the real-field deployments.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A Co-Simulation Framework for Steady-State Analyses of Multiple Droop-based MTdc Grids in Continental-Scale Systems
The growing scale and complexity of planning continental hybrid ac and multi-terminal dc (MTdc) systems require scalable steady-state modeling and analysis approaches not currently available in commercial tools. This paper presents a comprehensive multi-fidelity model-conversion framework that enables the efficient transition of MTdc grid models from production cost modeling (PCM) and approximated ac power flow to detailed ac–MTdc power flow for large-scale planning studies. The core of this framework is a scalable co-simulation approach that, for the first time, enables power flow analysis in continental-scale ac–MTdc systems. It seamlessly couples commercial ac solvers with a detailed MTdc grid model that incorporates droop-based control and current-limiting strategies of multiple meshed MTdc grids. Leveraging this capability, an evaluation framework to systematically assess and compare different MTdc power redispatch strategies under ac and dc contingencies is introduced. The proposed framework and algorithm are evaluated using a combined Western and Eastern Interconnection system with 11 MTdc grids of various sizes, showing a coherent transition from PCM to detailed ac–MTdc power flow and improved system performance in voltage regulation and line overload mitigation following typical contingencies.
Nguyen, Quan H.↗
A Review on Protection Challenges on Transmission Lines Connected to Inverter Based Resources
The increased penetration of inverter-based resources (IBRs) connected to transmission grids is challenging how traditional electric power systems operate. Such systems were originally designed based on the dominant presence of synchronous generators. Some main challenges include the increased concerns about system stability due to the reduced system inertia caused by IBRs and the reduced protection reliability caused by the non-deterministic fault current response of IBRs. The protection relays’ algorithms have been designed and validated based on well-known fault current characteristics of synchronous generations, while the short-circuit responses of IBRs heavily depend on their vendor-specific control schemes, which are mainly set to protect inverter semiconductor switches and DC components. The magnitude of short current that IBRs contribute is typically between 1.1–1.5 times the rated current that may behave unstably and incoherently with the voltages. The control scheme of the IBRs also controls the active (P) and reactive (Q) support during system voltage sag and swell conditions. These characteristics challenge not only protective relay schemes but also existing short-circuit software tools to correctly model IBRs for fault studies and protection coordination analyses. Utilities, university researchers, research institutes, and relay manufacturers have performed studies to investigate different aspects of high IBR penetration. Almost all studies support 1) creating international and national standards to regulate the IBRs, 2) revising engineering tools to address shortcomings, and 3) adjusting the protective relay settings to resolve protection problems. This paper summarizes the studies and research conducted in recent years to quantify the impact of IBR penetration on transmission line protection and to identify potential solutions to improve the dependability and reliability of grid protection systems.
14 SOLAR ENERGY↗
Microstructural characterization of the oxidation of nuclear graphite under chronic and accident conditions via XCT and synchrotron XCT
Graphite is a candidate material to moderate fast neutrons and for structural components in the US next-generation graphite-moderated reactors. A graphite core is conceived as a large formation of interconnected bricks that primarily serves as the moderator of fast neutrons, holds instrumentation, fuel elements, control rods, and is a receptacle for molten salts for Molten Salt Reactors (MSRs) designs. During the operation of a graphite-moderated power plant, graphite components might be subjected to chronic oxidation during normal operating conditions or aggressive oxidation as a result of accidental ingress of air that reacts vigorously with the graphite core. Using synchrotron, x-ray computed tomography (XCT), this research systematically characterized microstructural changes that accompanied these two oxidation scenarios. Chronic oxidation was studied by characterizing IG-110, PCEA, and NBG-18 specimens that were gradually oxidized in air at a low temperature (520°C). The accidental ingress of air into the graphite reactor was simulated by subjecting the grades mentioned above to high-temperature oxidation at approximately 750°C. This research is the first, in situ, systematic characterization of nuclear graphite microstructural evolution that can be associated with the two possible oxidation scenarios and provide insight into related repercussions. The results show that the microstructure and pore connectivity influence the rate of oxidation and evolution of the microstructure under the two oxidation regimes. These results are crucial to understanding which grades are more resilient to each type of oxidation and documenting the damage created in the graphite.
Arregui Mena, Jose'↗
A Review on Protection Challenges of Transmission Lines Connected to Inverter-Based Resources
Utilities, university researchers, research institutes, and relay manufacturers have performed studies to investigate different aspects of high IBR penetration. Almost all studies support 1) creating international and national standards to regulate the IBRs, 2) revising engineering tools to address shortcomings, and 3) adjusting the protective relay settings to resolve protection problems. This paper summarizes the studies and research conducted in recent years to quantify the impact of IBR penetration on transmission line protection and to identify potential solutions to improve the dependability and reliability of grid protection systems.
14 SOLAR ENERGY↗
Developing a Reduced 240-Bus WECC Dynamic Model for Frequency Response Study of High Renewable Integration
The ongoing changes in the generation resource mix, driven by the rapid adoption of inverter-based resources (IBR) as well as the early retirement of synchronous generators, are bringing new challenges to the planning and operation of bulk electric power systems. Consequently, there is an increasing need to understand, design, and quantify the reliability service provision from IBRs by performing integrated scheduling and dynamic simulations. However, test systems that have consistent scheduling and dynamic models rarely exist largely because of the decoupled nature of the two simulations on a synchronous generator-dominated system. This paper develops the dynamic model of a reduced Western Electricity Coordinating Council (WECC) system. In conjunction with the existing scheduling model, it is suitable for integrating scheduling and dynamic simulations. The reduced 240-bus WECC model reflects the generation resource mix of the Western Interconnection as of 2018. Moreover, the developed dynamic model is validated against field frequency events measured by FNET/GridEye and preserves the dominant inter-area oscillation mode in WECC.
dynamic simulation↗
Multi–Stage Optimization of Pore Size and Shape in Pore–Space–Partitioned Metal–Organic Frameworks for Highly Selective and Sensitive Benzene Capture
Compared to exploratory development of new structure types, pushing the limits of isoreticular synthesis on a high-performance MOF platform may have higher probability of achieving targeted properties. Multi-modular MOF platforms could offer even more opportunities by expanding the scope of isoreticular chemistry. However, navigating isoreticular chemistry towards best properties on a multi-modular platform is challenging due to multiple interconnected pathways. Here on the multi-modular pacs (partitioned acs) platform, we demonstrate accessibility to a new regime of pore geometry using two independently adjustable modules (framework-forming module 1 and pore-partitioning module 2). A series of new pacs materials have been made. Benzene/cyclohexane selectivity is tuned, progressively, from 4.5 to 15.6 to 195.4 and to 482.5 by pushing the boundary of the pacs platform towards the smallest modules known so far. The exceptional stability of these materials in retaining both porosity and single crystallinity enables single-crystal diffraction studies of different crystal forms (as-synthesized, activated, guest-loaded) that help reveal the mechanistic aspects of adsorption in pacs materials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Application Experiences on a GPU-Accelerated Arm-based HPC Testbed
This paper assesses and reports the experience of ten teams working to port, validate, and benchmark several High Performance Computing applications on a novel GPU-accelerated Arm testbed system. The testbed consists of eight NVIDIA Arm HPC Developer Kit systems, each one equipped with a server-class Arm CPU from Ampere Computing and two data center GPUs from NVIDIA Corp. The systems are connected together using InfiniBand interconnect. The selected applications and mini-apps are written using several programming languages and use multiple accelerator-based programming models for GPUs such as CUDA, OpenACC, and OpenMP offloading. Working on application porting requires a robust and easy-to-access programming environment, including a variety of compilers and optimized scientific libraries. The goal of this work is to evaluate platform readiness and assess the effort required from developers to deploy well-established scientific workloads on current and future generation Arm-based GPU-accelerated HPC systems. The reported case studies demonstrate that the current level of maturity and diversity of software and tools is already adequate for large-scale production deployments.
Elwasif, Wael↗
Nuclear Physics Network Requirements Review (Final Report)
The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. ESnet interconnects DOE national laboratories, user facilities, and major experiments so that scientists can use remote instruments and computing resources as well as share data with collaborators, transfer large datasets, and access distributed data repositories. ESnet is specifically built to provide Between July 2023 and October 2023, ESnet and the Nuclear Physics program (NP) of the DOE SC organized an ESnet requirements review of NP-supported activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the NP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.
97 MATHEMATICS AND COMPUTING↗
Design, Control and Application of Next Generation Qubits
Design, Control and Application of Next Generation Qubits Arun Bansil, Northeastern University (Principal Investigator) Claudio Chamon, Boston University (Co-Investigator) Adrian Feiguin, Northeastern University (Co-Investigator) Liang Fu, MIT (Co-Investigator) Eduardo Mucciolo, Univ. of Central Florida (Co-Investigator) Qimin Yan, Temple University (Co-Investigator) The quest for developing technologies for manipulating and storing information quantum mechanically is currently led by approaches that include Josephson-junctions, ion-traps, and qubits generated by defect spins in solids. Topological qubits, however, are inherently more robust to decoherence by environmental effects, and should be able to sprint ahead once practical barriers have been overcome. At the present stage of the development of the field, it is important to explore a variety of architectures and materials beyond the conventional paradigms in order to seed breakthroughs toward building a scalable quantum computer. Our comprehensive theoretical research program involved four interconnected thrusts as follows. • A materials discovery effort in two-dimensional compounds in search of materials to support Majorana zero modes and defect structures suitable as qubits. • Exploration of architectures for topological quantum computation by investigating both superconducting Majorana qubits, and robust platforms for braiding with new “meta-materials” built of arrays of Majorana qubits. • Investigation of properties of hybrid metal-organic qubits based on transition-metal centers in graphene, and molecular crystals of polyaromatic complexes with embedded transition-metal atoms. • Development of tensor-network and semiclassical approaches to study decoherence in the presence of random and dispersive spin baths, and NV centers in diamond. The full spectrum of theoretical and numerical approaches was used to address the goals of this project including first-principles, density-matrix-renormalization group, tensor networks, and data-driven high-throughput approaches using materials database and machine-learning.
36 MATERIALS SCIENCE↗
Progress of Gas Injection EOR Surveillance in the Bakken Unconventional Play—Technical Review and Machine Learning Study
Although considerable laboratory and modeling activities were performed to investigate the enhanced oil recovery (EOR) mechanisms and potential in unconventional reservoirs, only limited research has been reported to investigate actual EOR implementations and their surveillance in fields. Eleven EOR pilot tests that used CO2, rich gas, surfactant, water, etc., have been conducted in the Bakken unconventional play since 2008. Gas injection was involved in eight of these pilots with huff ‘n’ puff, flooding, and injectivity operations. Surveillance data, including daily production/injection rates, bottomhole injection pressure, gas composition, well logs, and tracer testing, were collected from these tests to generate time-series plots or analytics that can inform operators of downhole conditions. A technical review showed that pressure buildup, conformance issues, and timely gas breakthrough detection were some of the main challenges because of the interconnected fractures between injection and offset wells. The latest operation of co-injecting gas, water, and surfactant through the same injection well showed that these challenges could be mitigated by careful EOR design and continuous reservoir monitoring. Reservoir simulation and machine learning were then conducted for operators to rapidly predict EOR performance and take control actions to improve EOR outcomes in unconventional reservoirs.
Energy & Fuels↗
Tritiated Water Disposition Strategies
Tritium, a radioactive isotope of hydrogen, is typically confined within one or more confinement barriers. Tritium readily reacts with oxygen to form tritiated water or can exchange with protium or deuterium atoms in water to create tritiated water which is around 10,000 times more toxic than elemental tritium. Primary tritium confinement systems can create small volumes of highly tritiated water. Secondary confinement systems, like inert gloveboxes, will produce larger volumes of lower concentration tritiated water. Much larger volumes of tritiated water of very low tritium content are produced by tritium permeation/diffusion. Tritium from inside primary and secondary confinement barriers will diffuse from these systems into cooling water systems. Closed loop, recirculating cooling water systems will slowly accumulate tritium and create concentrations which exceed drinking water (or permitted discharge) concentrations. The cooling water systems designed as series of interconnected cooling loops that can slowly transfer tritium from one cooling loop to another cooling loop through heat exchangers. These large volumes of tritiated water may be above federal discharge limits and also lack convenient disposition pathways. This document will discuss tritiated water management strategies from the perspective of large volume, low tritium concentrations that exceed drinking water or permitted discharge limits. Applicable US regulatory requirements for a Molybdenum-99 (Mo-99) production facility concerning tritiated water are also cited. Tritiated water disposition options, based on typical waste minimization strategies will guide dispositions options. A Case Study example is presented to illustrate the pros and cons of several disposition options. The report does not recommend any particular disposition pathway but discusses strategies to be explored by a producer to guide selection of processes which best fits the needs of a particular waste stream.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Future foundries: A convergent manufacturing platform
This article introduces the Future Foundries platform developed at Oak Ridge National Laboratory, a first-generation research system designed to demonstrate convergent manufacturing. Convergent manufacturing brings together additive, subtractive, and transformative processes in a digitally interconnected environment to enable end-to-end production workflows. By linking traditionally discrete steps, convergent platforms accelerate production, improve repeatability, and support high-mix, low-volume manufacturing. The Future Foundries platform exemplifies this vision in practice by combining four modular, vendor-agnostic process cells that include robotic WAAM, induction heating, optical metrology, and machining, coordinated through an automated pallet handler and a ROS 2-based digital thread. This architecture provides the flexibility and scalability needed for agile production in small and medium-sized manufacturing enterprises and for field deployable manufacturing. Two case studies illustrate the platform’s capabilities. The first presents an integrated workflow for fabricating, transforming, and repairing critical replacement components, showing how consolidated thermal, additive, inspection, and machining operations reduce manual part handling and streamline process flow. The second case study highlights coordinated multi-part production enabled by automated pallet logistics and multi-cell scheduling. Together, these examples showcase convergent manufacturing as a practical and scalable strategy for strengthening domestic casting and forging capacity, improving supply-chain resilience, and enabling rapid, adaptable production of mission-critical components.
Convergent manufacturing↗