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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

SHASTA-HELP: Hydrogen Estimator for Logistical Planning Tool

Underground reservoirs offer a promising option for medium- and long-term hydrogen storage that could potentially be safer and more cost-effective than surface alternatives. Currently, there are three underground hydrogen storage (UHS) facilities in the United States, which operate solely in salt caverns and store hydrogen primarily for industrial purposes. Salt formations favorable for geologic storage are geographically limited in the U.S. If a hydrogen economy is to develop, expansion of UHS to other geologic formations such as depleted gas fields and saline aquifers will be necessary to increase the availability of hydrogen storage. While research into the feasibility of storing hydrogen in these formations is ongoing, tools and methodologies are needed for characterizing the hydrogen storage potential in these reservoirs. We introduce the Hydrogen Estimator for Logistical Planning (HELP) tool from the Subsurface Hydrogen Assessment, Storage, and Technology Acceleration (SHASTA) project (https://edx.netl.doe.gov/shasta). SHASTA-HELP is a suite of web-based tools that have numerous capabilities for UHS project planning.

Haeri, Foad↗
DOE OSTI2025

Catastrophic Cooling Instability in Optically Thin Plasmas

The solar corona is the prototypical example of a low-density environment heated to high temperatures by external sources. The plasma cools radiatively, and because it is optically thin to this radiation, it becomes possible to model the density, velocity, and temperature structure of the system by modifying the MHD equations to include an energy source term that approximates the local heating and cooling rates. The solutions can be highly inhomogeneous and even multiphase because the well-known linear instability associated with this source term, thermal instability, leads to a catastrophic heating and cooling of the plasma in the nonlinear regime. Here we show that there is a separate, much simpler linear instability accompanying this source term that can rival thermal instability in dynamical importance. The stability criterion is the isochoric one identified by Parker (1953), and we demonstrate that cooling functions derived from collisional ionization equilibrium are highly prone to violating this criterion. If catastrophic cooling instability can act locally in global simulations, then it is an alternative mechanism for forming condensations, and due to its nonequilibrium character, it may be relevant to explaining a host of phenomena associated with the production of cooler gas in hot, low density plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Machine learning-based real-time kinetic profile reconstruction in DIII-D

Abstract Kinetic equilibrium reconstruction plays a vital role in the physical analysis of plasma stability and control in fusion tokamaks. However, the traditional approach is subjective and prone to human biases. To address this, the consistent automatic kinetic equilibrium reconstruction (CAKE) method was introduced, providing objective results. Nonetheless, its offline nature limits its application in real-time plasma control systems (PCSs). To address this limitation, we present RTCAKENN, a machine learning model that approximates 7 CAKE-level output profiles, namely pressure, inverse q , toroidal current density, electron temperature and density, carbon ion impurity temperature and rotation profiles, using real-time available inputs. The deep neural network consists of an encoder layer, where the scalars and interdependent inputs such as plasma boundary coordinates and motional Stark effect data are encoded using multi-layer perceptrons (MLPs), while profile inputs are encoded by 1D convolutional layers. The encoded data is passed through a MLP for latent feature extraction, before being decoded in the decoding layers, which consist of upsampling and convolutional layers. RTCAKENN has been implemented in the DIII-D PCS and our model achieves accuracy comparable to CAKE and surpasses existing real-time alternatives. Through clever dropout training, RTCAKENN exhibits robustness and can operate even in the absence of Thomson scattering data or charge exchange recombination data. It executes in under 8 ms in the real-time environment, enabling future application in real-time control and analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Intelligent Surrogate Model Development: Boosting Computational Efficiency for Autonomous Control of Advanced Reactors

Advanced reactors promise enhanced safety, greater efficiency, and waste reductions. To fully realize these benefits, it is crucial to address the need for autonomous or semi-autonomous control systems that require fewer operators. This research primarily supports the MARVEL autonomous control system, which requires real-time operation. However, the current RELAP5 reactor thermal hydraulic transient simulation is excessively time-consuming. Therefore, this study aims to leverage deep learning techniques to develop a surrogate model, providing a more efficient and accurate alternative for real-time performance. The model was trained using a combination of one-timestep prediction and scheduled sampling. It was then used for recursive prediction of the reactor state. This developed surrogate model significantly improves computational efficiency, achieving a 12 times acceleration.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Mechanical Characteristics of Additively Manufactured ODS 316L and 316H Alloys with and Without Post-build Processing

This research aims to explore an accelerated development path for oxide dispersion-strengthened (ODS) alloys by integrating additive manufacturing (AM) technologies with recent advances in ODS materials and traditional manufacturing methods. Novel AM and post-build processing routes have been developed for ODS austenitic alloys, specifically Fe-Cr-Ni alloys like 316L and 316H. Electron microscopy and mechanical characterizations were conducted to evaluate the effects of process variables on microstructure and properties, aiming for an economically feasible route property optimization. Traditionally, ODS alloy production involves multi-day high-energy mechanical milling of alloy powder with yttria (Y 2 O 3 ) followed by powder consolidation via extrusion or other methods and additional thermomechanical processing (TMP) for property control. Here, to address these challenges associated with this complex and costly approach, we propose exploring alternative, cost-effective processing routes focusing on AM and traditional TMP methods. The new ODS alloy processing routes have achieved up to a 400% increase in yield strength and a 60% increase in ultimate tensile strength compared to wrought stainless steels while still maintaining significant ductility and fracture toughness. This paper details the novel and economical AM-based processing routes for ODS austenitic alloys, combined with post-build TMPs, and discusses the mechanical and microstructural characteristics of the developed materials.

Byun, Thak Sang [Oak Ridge National Laboratory (OR↗
DOE OSTI2022

A hybrid inorganic–biological artificial photosynthesis system for energy-efficient food production

Artificial photosynthesis systems are proposed as an efficient alternative route to capture CO 2 to produce additional food for growing global demand. Here a two-step CO 2 electrolyser system was developed to produce a highly concentrated acetate stream with a 57% carbon selectivity (CO 2 to acetate), allowing its direct use for the heterotrophic cultivation of yeast, mushroom-producing fungus and a photosynthetic green alga, in the dark without inputs from biological photosynthesis. An evaluation of nine crop plants found that carbon from exogenously supplied acetate incorporates into biomass through major metabolic pathways. Coupling this approach to existing photovoltaic systems could increase solar-to-food energy conversion efficiency by about fourfold over biological photosynthesis, reducing the solar footprint required. This technology allows for a reimagination of how food can be produced in controlled environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Grid Forming Inverter: Laboratory-Scale Hardware Test Bed Setup and Weak Grid Operation

In recent times, the concept of grid forming inverters has gained popularity. Grid forming inverters have proven to be a promising alternative to the grid following inverters. In this paper, we present the hardware test bed implementation of grid forming inverter in islanding mode as well as in grid connected mode. The control structure includes inverter-level inner current control and outer voltage control, and plant-level P - f and Q - V droop control. The Q - V droop provides the voltage command, whereas P - f droop provides the frequency command and is also key for the synchronization process. While it is straightforward to set up the test bed for the islanded operation, it is a challenging process to set up the grid-forming inverter in the grid-connected mode. We present the key technologies and demonstrate the start-up process and weak grid operation using the hardware experiment results. Results from EMT model developed in MATLAB/SimPowerSystems are also presented for side-by-side comparison.

Mittal, Ratik↗
DOE OSTI2026

or-topas: Operations Research Toolkit for Pyomo Alternative Solutions

SAND2026-16702O OR-TOPAS: Operations Research Toolkit for Pyomo Alternative Solutions is a tool that enhances optimization applications defined by the Pyomo modeling library. It offers functions to generate optimal or near-optimal solutions, operating independently of Pyomo’s solver interface. Users can configure these functions with specific solver names and options, resulting in a custom solution object that returns a list of solutions. The OR-TOPAS library includes methods tailored to the properties of the model, such as binary integer programs versus linear programs, and specific solver interfaces like Gurobi. It does not provide models for specific applications, but it is applicable to a wide range of Pyomo optimization models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Siirola, John [Sandia National Lab. (SNL-CA), Live↗
DOE OSTI2022

The Third Assessment of the Effects of Climate Change on Federal Hydropower

Understanding the future changes in projected water supplies is a vital objective for federal hydropower facilities tasked with providing low-cost, reliable electricity across a large regional footprint that encompasses a growing customer base, alternative market structures for marketing the electricity, and a more diverse generation asset mix than was historically present when a majority of federal hydropower facilities were built. This study, The Third Assessment of the Effects of Climate Change on Federal Hydropower, directed by Section 9505 of the SECURE Water Act of 2009 (SWA), is the third quinquennial report on evaluating the effects of climate change on hydroelectric energy generated from 132 US federal hydropower plants marketed by four US Department of Energy (DOE) Power Marketing Administrations (PMAs). The technical assessment is conducted by DOE’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and Texas A&M University under the guidance of DOE’s Water Power Technologies Office. This study is the result of extensive consultation with the four federal PMAs (Bonneville Power Administration [BPA], Western Area Power Administration [WAPA], Southwestern Power Administration [SWPA], and Southeastern Power Administration [SEPA]), as well as other agencies, including federal hydropower owners/operators (the US Army Corps of Engineers, US Bureau of Reclamation [Reclamation]), US Geological Survey, and National Oceanic and Atmospheric Administration). The main findings of this assessment, along with the PMA administrators’ recommendations, will be included in a subsequent DOE report to Congress. The assessment method and the technical findings are described in this report.

13 HYDRO ENERGY↗
DOE OSTI2021

Separations Consortium: Lignin Rich Stream Fractionation and Purification

In support of the Bioenergy Technologies Office in converting lignin to fuels and chemicals, this project develops scalable separations based on membranes and Electordeionization (EDI) to recover low molecular weight (LMW) compounds from lignin rich streams. The project addresses three technology barriers in developing the bioeconomy; (1) Cost of production (2) Selective separation of organic acid species, and (3) Advanced bioprocess development. Specifically, membrane cascades using Tangential Flow Filtration (TFF) are investigated for the recovery of LMW lignin compounds from lignin rich streams such as Alkaline Pretreatment Liquor (APL), Reductive Catalytic Fractionation (RCF) oil, and Catalytic Oxidation oil. Process concepts, including dynamic filtration, are investigated to meet specific performance targets indicated by the consortium's Industrial Advisory Board for the membrane filtration including maintaining permeance > 1 LMH/bar and an overall cost target of < $1/kg of LMW lignin. EDI is investigated as an integral part of the membrane cascade to recover LMW aromatic acids and as an alternative to nanofiltration. Economic analysis of the processes is presented with a focus on minimizing energy consumption and capital expenditure. Furthermore, a sensitivity analysis is presented to identify key cost drivers and optimize holistic process operating conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Accelerating error correction in tomographic reconstruction

Abstract Spurred by recent advances in detector technology and X-ray optics, upgrades to scanning-probe-based tomographic imaging have led to an exponential growth in the amount and complexity of experimental data and have created a clear opportunity for tomographic imaging to approach single-atom sensitivity. The improved spatial resolution, however, is highly susceptible to systematic and random experimental errors, such as center of rotation drifts, which may lead to imaging artifacts and prevent reliable data extraction. Here, we present a model-based approach that simultaneously optimizes the reconstructed specimen and sinogram alignment as a single optimization problem for tomographic reconstruction with center of rotation error correction. Our algorithm utilizes an adaptive regularizer that is dynamically adjusted at each alternating iteration step. Furthermore, we describe its implementation in a software package targeting high-throughput workflows for execution on distributed-memory clusters. We demonstrate the performance of our solver on large-scale synthetic problems and show that it is robust to a wide range of noise and experimental drifts with near-ideal throughput.

Ali, Sajid (ORCID:0000000321864636)↗
DOE OSTI2026

Hydrogen applications in airport operations: a review using the Port Authority of New York and New Jersey as an illustrative airport system

Airports combine aircraft propulsion, ground operations, stationary power systems, and fuel logistics in ways that make emissions reduction technically and operationally complex. Existing studies often assess hydrogen applications in these areas separately, limiting understanding of the shared infrastructure, safety, and operational constraints that shape airport deployment. This review evaluates hydrogen across three airport-relevant operational domains: aviation propulsion, ground support equipment and vehicles, and stationary power systems. Within aviation propulsion, the review examines sustainable aviation fuel production and hydrogen-powered aircraft as two distinct hydrogen-relevant pathways. The Port Authority of New York and New Jersey is used as an illustrative airport system to relate the literature to a real operating context. Drawing on peer-reviewed studies, technical reports, demonstration projects, and public operational information, the review also includes screening-level calculations of hydrogen demand and potential CO 2 e reductions for selected applications. The findings show that hydrogen's role is highly application-specific. Near-term opportunities are strongest where hydrogen serves as a low-carbon process input, supports selected high-utilization ground equipment, or contributes to resilient stationary power-system configurations. Hydrogen-powered aircraft remain a longer-term option because storage, fueling infrastructure, certification, cost, and NO x management continue to constrain deployment. Across all domains, infrastructure readiness, fuel logistics, safety requirements, and leakage management emerge as recurring determinants of viability. Future research should focus on cross-domain infrastructure planning, comparative assessment of hydrogen against alternative pathways, improved treatment of leakage and non-CO 2 effects, and clearer safety and regulatory frameworks for airport deployment.

08 HYDROGEN↗
DOE OSTI2020

Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels

Biofuel and bioenergy systems are integral to most climate stabilization scenarios for displacement of transport sector fossil fuel use and for producing negative emissions via carbon capture and storage (CCS). However, the net greenhouse gas mitigation benefit of such pathways is controversial due to concerns around ecosystem carbon losses from land use change and foregone sequestration benefits from alternative land uses. Here, we couple bottom-up ecosystem simulation with models of cellulosic biofuel production and CCS in order to track ecosystem and supply chain carbon flows for current and future biofuel systems, with comparison to competing land-based biological mitigation schemes. Analyzing three contrasting US case study sites, we show that on land transitioning out of crops or pasture, switchgrass cultivation for cellulosic ethanol production has per-hectare mitigation potential comparable to reforestation and severalfold greater than grassland restoration. In contrast, harvesting and converting existing secondary forest at those sites incurs large initial carbon debt requiring long payback periods. We also highlight how plausible future improvements in energy crop yields and biorefining technology together with CCS would achieve mitigation potential 4 and 15 times greater than forest and grassland restoration, respectively. Finally, we show that recent estimates of induced land use change are small relative to the opportunities for improving system performance that we quantify here. While climate and other ecosystem service benefits cannot be taken for granted from cellulosic biofuel deployment, our scenarios illustrate how conventional and carbon-negative biofuel systems could make a near-term, robust, and distinctive contribution to the climate challenge.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Magnetic mesh generation and field line reconstruction for scrape-off layer and divertor modeling in stellarators

The design of divertor targets and baffles for optimal heat and particle exhaust from magnetically confined fusion plasmas requires a combination of fast, low-fidelity models (such as EMC3-Lite (Feng 2022 Plasma Phys. Control. Fusion 64 125012)) for scoping studies and high-fidelity ones (such as EMC3-EIRENE (Feng et al 2014 Contrib. Plasma Phys. 54 426–31)) for verification. Both of those approaches benefit from a magnetic flux tube mesh for fast interpolation and mapping of field line segments (Feng et al 2005 Phys. Plasmas 12 052505). A new automated mesh generator for unstructured quadrilateral flux tubes with adaptive refinement is presented and integrated into FLARE (Frerichs 2024 Nucl. Fusion 64 106034). For HSX with an extended first wall, it is found that several layers of flux tubes can span the entire half field period before splitting is required. This is an advantage over the traditional setup of the EMC3-EIRENE mesh where careful construction of several sub- domains is required already for the much tighter present first wall. In particular, there is no longer the need to manually construct a suitable outer boundary for the mesh. The divide and conquer paradigm with unstructured mesh layout offers a powerful alternative for fast head load approximation that is suitable for integration into optimization workflows. Further examples for W7-X and CTH demonstrate the versatile application range.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Technology Development and Field Monitoring in nZEB - US Country report IEA HPT Annex 49 Task 3

The International Energy Agency (IEA) Heat Pumping Technologies (HPT) Annex 49, “Design and Integration of Heat Pumps for Nearly Zero Energy Buildings,” deals with the application of heat pumps (HPs) as a core component of the HVAC system for nearly or net-zero energy buildings. This report covers the Task 3 activities of the US team. Three institutions are involved on the US team and have worked on the following projects. 1) Oak Ridge National Laboratory (ORNL) summarized development activities since the conclusion of IEA HPT Annex 40 for several integrated HP (IHP) systems - electric ground-source IHP and air-source IHP versions and engine-driven AS-IHP version. 2) The University of Maryland partnered with ORNL and Blue Bear Management to develop a personal cooling device called RoCo that can provide personalized conditioned air to occupants in inadequately or unconditioned environments. With RoCo, building facility management can elevate the HVAC thermostat settings without compromising occupants’ thermal comfort. Researchers have found that a 4°F increase in thermostat settings can save 12–30% energy savings. Therefore, RoCo is a promising technology that can help reduce building energy consumption and facilitate achievement of net-zero energy building performance. 3) The National Institute of Standards and Technology (NIST) is working on a field study effort on the NIST Net-Zero Energy Residential Test Facility. Two air-source split-system HPs were installed in a residential, net-zero energy home that was constructed as a laboratory on the NIST campus in Gaithersburg, Maryland. The first HP was a two-stage, 7 kW (2 ton), 15.8 seasonal energy efficiency ratio (SEER), 9.05 heating seasonal performance factor (HSPF) conventionally ducted system; the second HP was a variable-speed, 10.6 kW (3 ton), 14 SEER, 8.35 HSPF, high-velocity ducted system. These two systems operated side by side, using separate supply ducts and a common return duct, on a weekly alternating schedule to condition the home that was operated with very consistent simulated thermal loads. The team wanted to determine whether the high-velocity system could provide comparable energy-use efficiency to the conventional system. The results of this study showed that it did meet the required loads and had slightly greater efficiency; the average cooling coefficient of performance (COP) was (0.40 ± 0.11) higher, and the average heating COP was statistically equal. A new firmware was provided at the end of the heating season that greatly improved the performance of the high-velocity system; its average heating COP went from (1.8 ± 0.9) to (2.5 ± 1.1) at a 95% confidence level. The new firmware heating COP averaged (1.05 ± 0.23) higher than the old firmware over the same outdoor temperatures. The defrost performance is very different for these two systems, yet they consumed equivalent energy per HDD. The conventional system uses a timed-initiate, temperature-terminate algorithm with auxiliary electric resistive heating, whereas the high-velocity system uses calculated evaporator parameters with a hot-gas bypass before a full reverse-cycle defrost with no supplementary resistive heat.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Delivery of H - / H + Beams to Area A

We explore the relative merits of transporting the beam from the H + ion source and from the H - ion source to Area-A for low current applications. Transporting the H - beam to Area-A using the laser neutralization approach has some risk associated with it and will require some development. Alternative method of delivering H - beam to Area-A includes replacing LDBM00 bending magnet with kicker for sharing beam between Line D and modified Line A. Transporting the H + beam to Area-A will have significant impact on the operation the IPF facility and maintaining high pulse rate to IPF will require major modifications to the transition region of the accelerator and Drift Tube Linac.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)

In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Recent progress in the design of the K-DEMO divertor

The preliminary conceptual design of the Korean fusion demonstration reactor (K-DEMO) with a major radius of 6.8 m and the fusion power of 2200 MW has been studied since 2012. The overall configuration of the K-DEMO divetor system based on the ITER-like water-cooled tungsten technology is a double-null type symmetric divertor subdivided into 32 toroidal modules for the vertical maintenance. A detached divertor scenario with impurity seeding was considered as the primary approach for the power exhaust to reduce the peak heat flux lower than the engineering limit of 10 MW/m 2 . The power exhaust performance at the scrap off layer was estimated by using UEDGE-2D code, a two-dimensional fluid transport code for collisional edge plasma and neutral species like N, Ne, and Ar. Particle and heat flux on inboard and outboard divertor targets were calculated for the detached cased depending on parameters such as the impurity seeding rate, pumping rate, and the pedestal density. On the other hand, a magnetic solution like X-divertor, snowflake divertor, and super X-divertor to expand the plasma wet area was considered for K-DEMO since the detached divertor increasing a radiation fraction by impurity seeding might be able to be unstable. However, the extremely high current of poloidal coils was required more than the engineering limit, 20 MA, to form magnetic field lines for the alternative divertors. Based on the physical calculation of the edge plasma, engineering analyses were carried out to find out the thermal and structural reliability. The thermo-hydraulic analysis confirmed thermal stability, whether all comprising materials are operating within their allowable temperature windows when the case of the peak heat flux is set to 10 MW/m 2 on the outboard divertor target. The response surface optimization method derived two optimal design candidates employing two kinds of heat sink materials, respectively: the reduced activation ferritic martensitic (RAFM) steel and CuCrZr alloy. Additionally, the drawbacks and merits of the two materials were definite. The optimal design with applying RAFM steel was vulnerable to withstand thermal and mechanical loads since low thermal conductivity caused too thin thickness of the heat sink. On the other hand, the CuCrZr alloy has critical drawbacks in terms of activation and radioactive waste despite its high thermal conductivity. Meanwhile, preliminary electromagnetic (EM) analysis was carried out to estimate the EM loads caused by the abnormal behaviors of plasma since EM loads are one of the most critical external loads for designing a DEMO divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗