Some recent gaseous reactor fluid mechanics experiments.
Gaseous reactor fluid mechanics for nuclear rocket engines, discussing experiments on geometries used in open cycle engine for acceptable uranium loss rate
SEARCH · Search NASA
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.
Gaseous reactor fluid mechanics for nuclear rocket engines, discussing experiments on geometries used in open cycle engine for acceptable uranium loss rate
A methodology to create conceptual designs of benchmark critical experiments for advanced reactors nuclear data testing and validation was developed. A first concept was explored, pebble-bed high-temperature gas cooled reactor, based on the HTR-10 reactor. The very high correlation is a proof of concept that the design is similar to the application, and performing such critical experiments would help nuclear data testing and validation. This proof-of-concept was included in the IER-539 CED-1:Preliminary Design of a New Horizontal Split Table report. Other concepts could be explored if needed, such as Molten-salt reactor, Sodium-cooled fast reactor or Heat pipe reactors/Microreactor.
Criticality experiments are an important part of the nuclear data pipeline. A better understanding of fission (and better nuclear data) is extremely important for the nuclear industry. Criticality experiments play a role in improving this understanding.
The Scintillating Bubble Chamber (SBC) Collaboration is designing a new generation of low background, noble liquid bubble chamber experiments with sub-keV nuclear recoil threshold. These experiments combine the electronic recoil blindness of a bubble chamber with the energy resolution of noble liquid scintillation, and maintain electron recoil discrimination at higher degrees of superheat (lower nuclear recoil thresholds) than Freon-based bubble chambers. A 10-kg liquid argon bubble chamber has the potential to set world leading limits on the dark matter nucleon cross-section for 𝒪(GeV/c 2 ) masses, and to perform a high statistics coherent elastic neutrino nuclear scattering measurement with reactor neutrinos. This work presents a detailed calibration plan to measure the detector response of these experiments, combining photoneutron scattering with two new techniques to induce sub-keV nuclear recoils: nuclear Thomson scattering and thermal neutron capture.
Nuclear data are a vital component of predictive simulations used in applications like experiment design, stockpile stewardship, nuclear nonproliferation/safeguards, health physics, and criticality safety. A singular simulation requires the coalescence of different areas of nuclear data such as cross sections, angular distributions, and energy distributions of emitted neutrons for different materials and energy ranges. Improving nuclear data and thus reducing the uncertainty in simulated parameters could enable smaller, better-informed safety factors and ultimately reduce operational and procedural costs. There is a constant effort to garner a better understanding of the physical quantities represented by nuclear data through experiments. Integral experiment benchmarks use simulated and measured results to validate current nuclear data values. In the past, benchmarks primarily focused on the effective multiplication factor (k eff ); however, this limited scope has caused compensating errors and areas of nuclear data that lack validation. Compensating errors are inaccuracies in nuclear data that are obfuscated by cancellation when observing integrated values such as k eff . Diverse integral benchmark experiments that look for quantities of interest other than k eff and include multiple responses minimize the possibility of compensating errors and provides validation to areas of nuclear data previously lacking experimental validation. Benchmark experiments can be optimized during the design process to be highly dependent on specific areas of nuclear data. The dependence of a response in an experiment to a specific area/type of nuclear data is defined as sensitivity. A larger sensitivity means that nuclear data uncertainties will play a larger role in the response(s) resulting in larger bias. Currently, the sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®1 ) transport code are limited to responses of k eff and tallied values (e.g., flux, surface current). As a part of the EUCLID project, this work explores estimating list-mode nuclear data sensitivities that can be used to design experiments aimed to constrain and reduce compensating errors in nuclear data by focusing on responses other than k eff . Tallied values are ideal quantities that are estimated with detectors during experiments. List-mode data (a list of neutron collection times) are the direct output of detector systems in subcritical neutron noise experiments. Expanding MCNP sensitivity capabilities to include the sensitivity of responses estimated from list-mode data, such as the prompt neutron decay constant (α) and multiplicity estimates (S and D), enables more direct comparison of simulated and measured experimental quantities. Additionally, deterministic tools such as SENSMG are capable of obtaining sensitivities to a wide variety of responses; however, these tools cannot handle complex geometries due to the assumptions made in discretizing the phase-space variables of the Boltzman transport equation.
A nuclear power programme has many benefits, but it is a major undertaking that requires careful planning and preparation as well as a substantial investment in time. It also necessitates the establishment of a sustainable national infrastructure with committed and sustained financial and human resources. While nuclear power is not unique in this respect, it is different from other sources of energy because of the risks associated with the use of nuclear material, as well as the need for compliance with international legal instruments, internationally accepted nuclear safety standards, nuclear security guidance, and safeguards requirements. The IAEA’s Milestones in the Development of a National Infrastructure for Nuclear Power, IAEA Nuclear Energy Series No. NG-G-3.1 (Rev. 1), defines a phased approach that identifies 19 infrastructure issues that should be addressed in each of the three phases of the development of a nuclear infrastructure for a nuclear power programme. The publication Evaluation of the Status of National Nuclear Infrastructure Development IAEA Nuclear Energy Series NG-T-3.2 (Rev. 2) provides a methodology to determine the status of the infrastructure conditions covering all 19 issues identified in the Milestones Approach. A companion IAEA Implementing Guide, Establishing the Nuclear Security Infrastructure for a Nuclear Power Programme, IAEA Nuclear Security Series No. 19, provides guidance on the recommended actions to be taken by a State to establish an effective national nuclear security infrastructure for a nuclear power programme using the Milestones Approach. This publication is intended to provide guidance based on the experiences and good practices of Member States with embarking nuclear power programmes as well as Member States that are expanding their nuclear power programmes. The guidance is in the form of case studies, which highlight challenges, issues, and solutions identified by Member States as lessons learned for new nuclear power programmes. This TECDOC is designed to present the experiences of Member States to assist other Member States in developing a nuclear security programme. It addresses the key actions necessary to establish an effective national nuclear security infrastructure for a nuclear power programme consistent with the three phases of the IAEA Milestones Approach. The Member States that provided case studies in this document are at different stages in the development of a nuclear power programme.
ABSTRACT Nuclear data (ND) are the input data for neutron‐transport simulations to answer questions related to nuclear technologies. Subsets of ND, here > 20,000 data points, are validated with respect to thousands of criticality experiments that represent various applications on a small scale. The aim of validation with these experiments is to find errors in ND or methods. The key challenge here is that several hundreds of ND are used to simulate one integral value. Hence, one cannot clearly identify what ND are leading to bias in criticality measurements. In fact, a mistake in one nuclear‐data observable can be compensated with an error in another, and the predicted criticality value would still be predicted in agreement with experimental data. Random forest (RF) was previously employed to predict bias in criticality measurements using sensitivities of simulated criticality experiments to ND. The SHapley Additive exPlanations (SHAP) metric was then applied to attribute the importance of each ND experiment and observable to bias prediction. This, however, did not highlight what ND were jointly related to predicting bias. This is important as it could inform us about where compensating errors in ND could hide. We tackle this shortcoming here by first decomposing the ND sensitivities to integral‐experiment simulations into principal components. Then we use principal component projections to predict bias via the RF and SHAP. The SHAP values and principal components are employed to reconstruct detailed SHAP values for each ND observable. We demonstrate that these extended SHAP bias predictions are more robust, less noisy, and more efficient. In addition, we show that this approach accounts for covariance in ND sensitivities and automates the identification of where compensating errors could hide in ND.
Experiments with accelerated helium ions were performed in an effort to localize the site of initial radiation interactions in the eye that lead to light flash observations by astronauts during spaceflight. The character and efficiency of helium ion induction of visual sensations depended on the state of dark adaptation of the retina; also, the same events were seen with different efficiencies and details when particle flux density changed. It was concluded that fast particles cause interactions in the retina, particularly in the receptor layer, and thus give rise to the sensations of light flashes, streaks, and supernovae.
The Centrifugal Nuclear Thermal Rocket (CNTR) is one of few designs that could enable extremely rapid missions to Mars using currently available technologies. McCarthy conducted the first conceptual study of high performance nuclear thermal propulsion (NTP) and published his findings in 1954. High performance NTP was further investigated by Princeton researchers in the early 1960s and continued by other researchers throughout the 60s, 70s, and 80s. An interagency panel conducted in 1991 demonstrated the potential of liquid core nuclear rockets, such as the Liquid Annular Reactor System (LARS), to reach temperatures up to 5000 K and specific impulses (Isp) up to 2000 s. A more recent study of versatile NTP asserts that a similar propulsion system, the Centrifugal Gas Core Reactor (CGCR), can reach an estimated Isp of 1800 s[4]. An Isp of that magnitude significantly reduces travel times and consequently health risks to flight crews. The CNTR seeks to build on the work of previous liquid core NTP systems and aims to reach an Isp in the range of 1500 s to 1800 s while using hydrogen as the propellant. However, the CNTR is not limited to hydrogen and can instead utilize other volatiles such as ammonia, methane, or water at about half the Isp of hydrogen. This flexibility expands the CNTR’s mission range considerably by providing propellant storability and the potential for directly using volatiles available in-situ.
NuScale is requesting information on their Consolidated Innovative Nuclear Research (CINR) experiment. The CINR was awarded through the Nuclear Science User Facilities. Photos include the NuScale basket, insert, and instrumentation holder.
How do we accelerate scientific progress in the Nuclear Data (ND) field? By selecting via Machine Learning (ML) an optimum combination of differential and integral experiments to reduce ND uncertainties.
In nuclear fuels, U-Mo metallic fuels are used in new space reactor designs and new research reactor fuels. MITR, MURR, and NBSR reactors plan on converting from different HEU fuels to a U-Mo HALEU fuel. In spend nuclear fuel, 95 Mo is one of the 15 main absorbing fission products in irradiated LWR fuel. This makes it important for criticality safety studies in transportation and reprocessing. In structural materials. Molybdenum is found commonly in alloys that make up the structural materials of nuclear reactors such as type 316 SS. Molybdenum helps to improve high temperature performance and corrosion resistance.
The goal of this presentation is to show the feasibility of performing a critical experiment with a B 4 C/Aluminum alloy neutron absorber plate. The motivation of this experiment is to provide integral data on modern neutron absorber product “Boralcan” by Rio Tinto. In 2020, used in about 20% of spent fuel pools in the US, and in casks for storage and transportation in the US and in Europe. The added value of this experiment: Neutron absorber plate modeling method verification: homogeneous or not, a lot of potential savings by relaxing boron loading credit limits. No available critical benchmark involving Boralcan, other boron-related experiments are relatively old. Nuclear data validation for B, C, and Al in the form of B 4 C in Al matrix.
The completion of Vogtle Units 3 and 4, despite significant cost and schedule overruns, a major bankruptcy, and a pandemic, demonstrates that the U.S. nuclear industry can still develop new supply chains, train a highly skilled workforce, and build large nuclear power plants. Vogtle, being a first-of-a-kind (FOAK) plant, faced overruns, but FOAK overruns can decrease with more deployments through a combination of design standardization and modularization, transferring and implementing lessons learned between consecutive projects, and innovation. This report quantifies the potential cost and schedule reductions in future AP1000 plants in the US and identifies the barriers in achieving those reductions. It starts with a summary and analysis of the cost and construction timeline data for AP1000 plants that started construction in the United States (Vogtle) and China. Motivated by the steep schedule reductions from the first to second series of AP1000 plants in China, a cost reduction model was developed to quantify potential reductions for future AP1000 builds in the US. Results show that within about 3 more builds, AP1000s can become economically attractive in large markets in the U.S., without leveraging the Investment Tax Credit (ITC) or Production Tax Credit (PTC), and much sooner if these tax credits are available. Importantly the financial risks for future AP1000 builds in the US might be much smaller than observed in the FOAK plants. The study also identifies various barriers for future builds including the availability of a supply chain and a skilled workforce, and emphasizes the importance of making investments to gather and implement lessons learned between consecutive projects.
Accurate nuclear data are required for simulations of many applications including nuclear criticality safety. Actinide nuclear data at intermediate energies (from 1 to 100s of keV) are imprecise and inaccurate, because of scarce differential data, and an insufficient theory approach to capture the structures expected in the data to yield evaluated nuclear data, and lack of integral data for proper validation. This is a known deficiency but has proved challenging to address. More specifically, only 5% of integral experiments in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmark suite address intermediate energies (Fig. 1). Associated calculated effective multiplication factor, k eff , values for these experiments are far outside the experimental uncertainties and are 25× further from experiment than for fast energies. These differences could either stem from systematic biases in nuclear data, experiments or both. The goal of the PARADIGM (PARallel Approach of Differential and InteGral Measurements) project is to significantly reduce (by more than tens of percent) the uncertainties of intermediate energy actinide nuclear data. The PARADIGM project designed and intends to execute LANSCE (Los Alamos Neutron Science CEnter) and NCERC (National Criticality Experiments Research Center) intermediate experiments in parallel. They will specifically address a high priority nuclear data need—reducing bias and uncertainty in intermediate plutonium nuclear data. The two experiment will achieve that by informing each other and nuclear theory. By doing all these steps in parallel, the timeline to deliver improved nuclear data to users will significantly be reduced. This work will focus on the integral experiment final design and the balance of design and modeling simplicity while minimizing experiment uncertainty.
Compared to other neutrino sources, the huge anti-neutrino fluxes at nuclear reactor based experiments empower us to derive stronger bounds on non-standard interactions of neutrinos with electrons mediated by light scalar/vector mediators. At neutrino energy around 200 keV reactor anti-neutrino flux is at least an order of magnitude larger compared to the solar flux. The atomic and crystal form factors of the detector materials related to the details of the atomic structure becomes relevant at this energy scale as the momentum transfers would be small. Non-standard neutrino-electron interaction mediated by light scalar/vector mediator arises naturally in many low-scale models. We also propose one such new model with a light scalar mediator. Here, we investigate the parameter space of such low-scale models in reactor based neutrino experiments with low threshold Ge and Si detectors, and find the prospect of probing/ruling out the relevant parameter space by finding the projected sensitivity at 90% confidence level by performing a $χ$ 2 -analysis. We find that a detector capable of discriminating between electron recoil and nuclear recoil signal down to a very low threshold such as 5 eV placed in reactor based experiment would be able to probe a larger region in parameter space compared to the previously explored region. A Ge (Si) detector with 10 kg-yr exposure and 1 MW reactor anti-neutrino flux would be able to probe the scalar and vector mediators with masses below 1 keV for coupling products $\sqrt{g_vg_e}$ ~ 1 × 10 -6 (9.5 × 10 -7 ) and 1 × 10 -7 (8 × 10 -8 ), respectively.
Among the diverse advanced nuclear reactor concepts being developed are designs that expect to operate at much higher temperatures than conventional light-water reactors, and therefore require alternative materials for components capable of withstanding these extreme temperatures. Insulation is one such component where alternative high-temperature industrial composites are being considered. Low-power experiments can provide an opportunity for advancing our understanding of material behavior under irradiation; however, these experiments are not without occupational hazards. The focus of this paper is the potential for activation of insulating composites when exposed to neutron fluence during reactor experiments, and to discuss the subsequent contamination of the testing area. This paper will also discuss practical measures for preventing the creation and inhalation of activated particulate matter (i.e., dust), such as engineering and administrative controls and personal protective equipment. This paper evaluates the suitability of several insulation materials for use in reactor experiments based on their activation from neutron irradiation. The materials considered are Pyrogel XTE by Aspen Aerogel, Cerablanket and Kaowool by Morgan Advanced Materials, Thermo-12 Gold by Johns Manville, and Maxsil CF6-2000 by McAllister Mills. Although these materials are not yet widely used in the nuclear industry, they are common in other industries due to their thermal insulating properties. These materials produce dust while handling that can pose health and safety hazards, which could be further exacerbated by activation. The analysis presented in this paper utilizes a deterministic method developed to predict the activation source term of the provided insulation materials. The method calculates the atomic density of each element within the composites and simulates their exposure to a specified neutron flux density representative of low power experimental conditions. During the irradiation phase and throughout the extensive cooling period, neutron absorptions and nuclear decays are tracked for relevant isotopes. The residual activity within each composite is then assessed to identify the material with the lowest potential radiological hazard to workers. Dust will be created during installation and removal of insulating materials and may also be generated during the experiment. Contamination of surrounding surfaces due to dispersion is highly likely unless preventative measures are taken. The results of this analysis are used to estimate an internal dose from inhalation of activated dust, which is significantly lower than the allowable whole-body dose. However, the risk of internal exposure may increase if the dust becomes a transport vector for nuclear material. The goals of this paper are to enhance the understanding of the potential activation and contamination hazards from the use of these insulating materials in low-power nuclear experiments and to foster safer work environments through informed decision-making and strategic planning. This work ultimately contributes to a broader understanding of how new non-nuclear materials for advanced reactors impact the radiological safety of co-located workers, helping to ensure the responsible management of radioactive materials during installation and decommissioning activities.
Investigations of various phases of gaseous nuclear rocket technology have been conducted. The principal research efforts have recently been directed toward the closed-cycle, vortex-stabilized nuclear light bulb engine and toward a small-scale fissioning uranium plasma experiment that could be conducted in the Los Alamos Scientific Laboratory's Nuclear Furnace. The engine concept is based on the transfer of energy by thermal radiation from gaseous fissioning uranium, through a transparent wall, to hydrogen propellant. The reference engine configuration is comprised of seven unit cavities, each having its own fuel transparent wall and propellant duct. The basic design of the engine is described. Subsequent studies performed to supplement and investigate the basic design are reported. Summaries of other nuclear light bulb research programs are included.