Search NASA⌕ Search

SEARCH · Search NASA

Results for “ENFORCEMENT”

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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Simulation process and data flow for a large system dynamics model

This paper documents the workflow and supporting technologies that a large system dynamics model, the biomass scenario model, employs to streamline the data preparation, simulation, quality control, and analysis process at the National Renewable Energy Laboratory. The workflow centers on automation of routine aspects of the flow of data between data stores, simulations, and visualizations. It enforces quality checks on data, reproducibility of computations, and traceability of results, while maintaining complete archives of modeling and analysis artifacts. The resulting frictionless simulation/analysis environment supports large-scale sensitivity analysis, interactive creation of ensembles of simulations, and rapid visualization-based exploration of simulation results.

09 BIOMASS FUELS↗
DOE OSTI2020

A phenomenological rate of injection model for predicting fuel injection with application to mixture formation in light-duty diesel engines

Fuel injection rate laws are one of the most important pieces of information needed when modeling engine combustion with computational fluid dynamics. In this study, a simple phenomenological model of a common-rail injector was developed and calibrated for the Bosch CRI2.2 platform. The model requires three tunable parameter fits, making it relatively easy to calibrate and suitable for injector modeling when high-fidelity information about the internal injector’s geometry and electrical circuit details are not available. Each injection pulse is modeled as a sequence of up to four stages: an injection needle mechanical opening transient, a full-lift viscous flow inertial transient, a Bernoulli steady-state stage, and a needle descent transient. Parameters for each stage are obtained as polynomial fits from measured injection rate properties. The model enforces total injected mass, and the intermediate stages are only introduced if the injection pulse duration is long enough. Experimental rates of injection from two separate campaigns on the same injector were used to calibrate the model. The model was first validated against measured injection rate laws featuring pilot injections, short partially premixed combustion pulses, and conventional diesel combustion injection strategies. Then, it was employed as an input to engine computational fluid dynamics simulations, which were run to simulate experiments of mixture formation in an optically accessible light-duty diesel engine. It was found that, though simple, this model is capable of predicting both pilot and main injection pulse mass flow rates well: the simulations yielded accurate predictions of in-cylinder equivalence ratio distributions from injection strategies for both partially premixed combustion and pilot injections. Also, once calibrated, the model produced appropriate results for a wide range of injected mass and rail pressure values. Finally, it was observed that usage of such a relatively simple model can be a good choice when high-fidelity injection rate input and highly detailed information of the injector’s geometry and operation are not available, particularly as noticeable discrepancies can be present also among different experimental campaigns on similar hardware.

42 ENGINEERING↗
DOE OSTI2018

Alignment-free genome comparison enables accurate geographic sourcing of white oak DNA

Background: The application of genomic data and bioinformatics for the identification of restricted or illegally-sourced natural products is urgently needed. The taxonomic identity and geographic provenance of raw and processed materials have implications in sustainable-use commercial practices, and relevance to the enforcement of laws that regulate or restrict illegally harvested materials, such as timber. Improvements in genomics make it possible to capture and sequence partial-to-complete genomes from challenging tissues, such as wood and wood products. Results: In this paper, we report the success of an alignment-free genome comparison method, d 2; that differentiates different geographic sources of white oak (Quercus) species with a high level of accuracy with very small amount of genomic data. The method is robust to sequencing errors, different sequencing laboratories and sequencing platforms. Conclusions: This method offers an approach based on genome-scale data, rather than panels of pre-selected markers for specific taxa. The method provides a generalizable platform for the identification and sourcing of materials using a unified next generation sequencing and analysis framework.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

The CompTox Chemistry Dashboard: a community data resource for environmental chemistry

Despite an abundance of online databases providing access to chemical data, there is increasing demand for highquality, structure-curated, open data to meet the various needs of the environmental sciences and computational toxicology communities. The U.S. Environmental Protection Agency’s (EPA) web-based CompTox Chemistry Dashboard is addressing these needs by integrating diverse types of relevant domain data through a cheminformatics layer, built upon a database of curated substances linked to chemical structures. These data include physicochemical, environmental fate and transport, exposure, usage, in vivo toxicity, and in vitro bioassay data, surfaced through an integration hub with link-outs to additional EPA data and public domain online resources. Batch searching allows for direct chemical identifer (ID) mapping and downloading of multiple data streams in several diferent formats. This facilitates fast access to available structure, property, toxicity, and bioassay data for collections of chemicals (hundreds to thousands at a time). Advanced search capabilities are available to support, for example, non-targeted analysis and identifcation of chemicals using mass spectrometry. The contents of the chemistry database, presently containing ~ 760,000 substances, are available as public domain data for download. The chemistry content underpinning the Dashboard has been aggregated over the past 15 years by both manual and auto-curation techniques within EPA’s DSSTox project. DSSTox chemical content is subject to strict quality controls to enforce consistency among chemical substance-structure identifers, as well as list curation review to ensure accurate linkages of DSSTox substances to chemical lists and associated data. The Dashboard, publicly launched in April 2016, has expanded considerably in content and user trafc over the past year. It is continuously evolving with the growth of DSSTox into high-interest or data-rich domains of interest to EPA, such as chemicals on the Toxic Substances Control Act listing, while providing the user community with a fexible and dynamic web-based platform for integration, processing, visualization and delivery of data and resources. The Dashboard provides support for a broad array of research and regulatory programs across the worldwide community of toxicologists and environmental scientists.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A novel physics-based and data-supported microstructure model for part-scale simulation of laser powder bed fusion of Ti-6Al-4V

The elasto-plastic material behavior, material strength and failure modes of metals fabricated by additive manufacturing technologies are significantly determined by the underlying process-specific microstructure evolution. In this work a novel physics-based and data-supported phenomenological microstructure model for Ti-6Al-4V is proposed that is suitable for the part-scale simulation of laser powder bed fusion processes. The model predicts spatially homogenized phase fractions of the most relevant microstructural species, namely the stable β-phase, the stable α s -phase as well as the metastable Martensite α m -phase, in a physically consistent manner. In particular, the modeled microstructure evolution, in form of diffusion-based and non-diffusional transformations, is a pure consequence of energy and mobility competitions among the different species, without the need for heuristic transformation criteria as often applied in existing models. The mathematically consistent formulation of the evolution equations in rate form renders the model suitable for the practically relevant scenario of temperature- or time-dependent diffusion coefficients, arbitrary temperature profiles, and multiple coexisting phases. Due to its physically motivated foundation, the proposed model requires only a minimal number of free parameters, which are determined in an inverse identification process considering a broad experimental data basis in form of time-temperature transformation diagrams. Subsequently, the predictive ability of the model is demonstrated by means of continuous cooling transformation diagrams, showing that experimentally observed characteristics such as critical cooling rates emerge naturally from the proposed microstructure model, instead of being enforced as heuristic transformation criteria. Eventually, the proposed model is exploited to predict the microstructure evolution for a realistic selective laser melting application scenario and for the cooling/quenching process of a Ti-6Al-4V cube of practically relevant size. Numerical results confirm experimental observations that Martensite is the dominating microstructure species in regimes of high cooling rates, e.g., due to highly localized heat sources or in near-surface domains, while a proper manipulation of the temperature field, e.g., by preheating the base-plate in selective laser melting, can suppress the formation of this metastable phase.

Inverse parameter identification↗
DOE OSTI2023

Elucidating regulatory processes of intense physical activity by multi-omics analysis

Abstract Background Physiological and biochemical processes across tissues of the body are regulated in response to the high demands of intense physical activity in several occupations, such as firefighting, law enforcement, military, and sports. A better understanding of such processes can ultimately help improve human performance and prevent illnesses in the work environment. Methods To study regulatory processes in intense physical activity simulating real-life conditions, we performed a multi-omics analysis of three biofluids (blood plasma, urine, and saliva) collected from 11 wildland firefighters before and after a 45 min, intense exercise regimen. Omics profiles post- versus pre-exercise were compared by Student’s t -test followed by pathway analysis and comparison between the different omics modalities. Results Our multi-omics analysis identified and quantified 3835 proteins, 730 lipids and 182 metabolites combining the 3 different types of samples. The blood plasma analysis revealed signatures of tissue damage and acute repair response accompanied by enhanced carbon metabolism to meet energy demands. The urine analysis showed a strong, concomitant regulation of 6 out of 8 identified proteins from the renin-angiotensin system supporting increased excretion of catabolites, reabsorption of nutrients and maintenance of fluid balance. In saliva, we observed a decrease in 3 pro-inflammatory cytokines and an increase in 8 antimicrobial peptides. A systematic literature review identified 6 papers that support an altered susceptibility to respiratory infection. Conclusion This study shows simultaneous regulatory signatures in biofluids indicative of homeostatic maintenance during intense physical activity with possible effects on increased infection susceptibility, suggesting that caution against respiratory diseases could benefit workers on highly physical demanding jobs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Progerin, the protein responsible for the Hutchinson-Gilford progeria syndrome, increases the unrepaired DNA damages following exposure to ionizing radiation

Introduction: Progerin, the protein responsible for the Hutchinson-Gilford Progeria Syndrome (HGPS), is a partially deleted form of nuclear lamin A, and its expression has been suggested as a cause for dysfunctional nuclear membrane and premature senescence. To examine the role of nuclear envelop architecture in regulating cellular aging and DNA repair, we used ionizing radiation to increase the number of DNA double strand breaks (DSBs) in normal and HGPS cells, and analyzed possible relationship between unrepaired DSBs and cellular aging. Results: We found that HGPS cells are normal in repairing a major fraction of radiation-induced double strand breaks (M-DSBs)but abnormal to show increased amount of residual unrepaired DSBs (R-DSBs). Such unrepaired DSBs were 2.6 times (CI 95 %: 2.2–3.2) higher than that in normal cells one week after the irradiation, and 1.6 times (CI 95 %: 1.3–1.9) higher even one month after the irradiation. These damages tend to increase as the nuclear envelope become abnormal, a characteristic of both HGPS and normal human cells which undergo replicative senescence. The artificial, enforced over-expression of progerin further impaired the repair of M-DSBs, implying lamin A-associated nuclear membrane has an important role for DNA DSB repair. Introduction of telomerase gene function in HGPS cells reversed such aging phenotypes along with upregulation of lamin B1 and downregulation of progerin, which is a hallmark of young cells. Conclusion: We suggest that lamin A- or progerin-associated nuclear envelope is involved in cellular aging associated with DNA damage repair.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Probabilistic Reasoner Based on Bayes Risk for Damage Detection in Structural Systems

Structural health monitoring (SHM) systems are used to inform operation of structural systems subject to loads and environments that may affect their integrity. SHM systems rely on continuous monitoring of the structure to determine its health state. These systems are often coupled with a model of the deployed structure to determine the consequences of changes in the system by forecasting the response to future states. These models, which may be thought of as digital twins, need to be updated to reflect the latest state of the structural system. This work makes use of an uncertainty-aware machine learning model that enforces distance preservation of the original input space to determine deviations from the training data input space distributions. This workflow enables domain shift detection to determine whether damage is present in the structure. The uncertainty metrics generated by this network are then used in a Bayes risk framework to design an optimal damage detector given cost and risk considerations. The approach is demonstrated on a computational example with simulated damage.

Najera-Flores, David [ATA Engineering, Inc.]↗
DOE OSTI2020

Data for Training and Testing Radiation Detection Algorithms in an Urban Environment

The US government routinely performs radiological response deployments to search for the presence of illicit nuclear materials (e.g., highly enriched uranium and weapons-grade plutonium) in a specified area. The deployments can be intelligence driven, in support of law enforcement, and for planned events such as WrestleMania, presidential inaugurations, or political conventions. In a typical deployment, radiation detection systems carried by human operators or mounted on vehicles move in a clearing pattern through the search area. Search teams rely on radiation detection algorithms running on these systems in real time to alert them to the presence of an illicit threat source. The detection and identification of sources is complicated by large variation of natural radiation background throughout a search area and the potential presence of localized non-threat sources such as patients undergoing treatment with medical isotopes. As a result, detection algorithms must be carefully balanced between missing real sources (false negatives) and reporting too many false alarms (false positives).The purpose of this data set is to spur innovations in detecting, identifying, and localizing nuclear materials inurban search missions.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2012

Nonlinear Acceleration of a Continuous Finite Element Discretization of the Self-Adjoint Angular Flux Form of the Transport Equation

Nonlinear acceleration of a continuous finite element (CFE) discretization of the transport equation requires a modification of the transport solution in order to achieve local conservation, a condition used in nonlinear acceleration to define the stopping criterion. In this work we implement a coarse-mesh finite difference acceleration for a CFE discretization of the second-order self-adjoint angular flux (SAAF) form of the transport equation and use a postprocessing to enforce local conservation. Numerical results are given for one-group source calculations of one-dimensional slabs. We also give a novel formal derivation of the boundary conditions for the SAAF.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Extension of the PINN diffusion model to k-eigenvalue problems

This paper extends our recent work on the Physics-Informed Neural Networks (PINN) approach for the fixed source diffusion models and applies it to the diffusion theory based k-eigenvalue problems. To make the PINN equitable for the eigenvalue problems, we introduce a novel integral regularization term to the loss function in the framework, and allow the direct inference of the principal eigenvalue and the associated eigenfunction. The regularization term enforces a pre-defined value on the integration of the model predictions, and this value can be directly related to a physical property of the system. We also introduce an additional learnable parameter to approximate the principal eigenvalue. As a proof of principle, we solve the one-group two-dimensional k-eigenvalue neutron diffusion equation in this work. We then provide two numerical examples to demonstrate the applicability of the PINN approach. In each example, we solve the k-eigenvalue diffusion equation in a multi-region configuration constrained with a set of Robin boundary conditions for generality. We use a FEM solution based on the power-iteration method to verify the results of the PINN solution. The results showed relative percentage error in the predicted eigenvalue of about 0.77% and about 1.2% for example 1 and example 2, respectively. The mean absolute error in the predicted flux for example 1 is ∼ 0.002 and for example 2 is ∼ 0.0024. These results indicate some preliminary successes of the PINN application to k-eigenvalue problems. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Transitioning from Cobalt-60 to X-Ray or E-Beam for Medical Sterilization: Filling Data and Education Gaps

The Office of Radiological Security (ORS) within the U.S. DOE’s National Nuclear Security Administration (NNSA) is charged to “work with government, law enforcement, and businesses across the globe to protect radioactive sources used for medical, research, and commercial purposes; remove and dispose of disused radioactive sources; and reduce the global reliance on high activity radioactive sources through the promotion of viable non-radioisotopic alternative technologies.” In this effort, the NNSA/ORS, along with the Office of Defense Nuclear Nonproliferation R&D, has been working with government and private entities that utilize gamma-ray irradiators in areas that include blood irradiation, radiotherapy, biology research, well logging, and radiation processing to consider alternative technologies that do not depend upon radioactive materials. In the medical device industry, nearly 50% of products are sterilized with ethylene oxide, 40.5% with cobalt-60 gamma-rays, 4.5% with electron-beam (e-beam), and <1% with X-ray.(1,2) The cobalt-60 irradiation facilities use an estimated 150 MCi of isotope to sterilize approximately 200 million cubic feet of product annually.(3) Due to growing safety regulations governing cobalt-60 use, continued advancements in e-beam and X-ray accelerator technology, and the greater irradiation durations and costs for cobalt-60 irradiation compared to e-beam and X-ray, switching to these non-radionuclide modalities is increasingly economically competitive. However, this breakdown of 40.5% cobalt-60 and 5.5% accelerator for product sterilization illustrates the difficulty that market forces and industry players have had in overcoming barriers in transitioning to non-nuclide alternatives. Besides those associated with construction of new e-beam and X-ray facilities, significant financial and regulatory obstacles are also associated with the irradiation and comprehensive testing of product constituent polymers and elastomers. The standards associated with product material performance testing are the Association for the Advancement of Medical Instrumentation (AAMI) Technical Information Report 17 (TIR 17), and its referenced American Society for Testing and Materials (ASTM) polymer testing standards. In the study now underway, and the subject of this article, the NNSA/ORS provided R&D funding to the Pacific Northwest National Laboratory (PNNL) in partnership with university researchers, leading medical product manufacturers, accelerator manufacturers, and contract sterilizers. The resulting Team Nablo (in memory of Sam Nablo) includes individuals representing PNNL, Becton Dickinson (BD), Johnson & Johnson, Stryker, Texas A&M University (TAMU), Steri-Tek, Mevex, Ion Beam Applications (IBA), and Sterigenics. The goals of this study are to 1) Identify specific polymer and/or elastomer-based medical products that are currently sterilized with gamma-rays, and for which there are data gaps and would be of greatest industry impact, 2) Work with relevant ASTM subcommittees for guidance and for potential standard revision, 3) Work with an appropriate Food & Drug Administration (FDA) office for potential collaboration on a guidance document for device manufacturers, 4) Measure the physical effects that product materials exhibit when they are given sterilization-level radiation doses from cobalt-60, e-beam or X-ray, and determine whether these effects would preclude the use of e-beam or X-ray for sterilization, 5) Communicate the resulting scientific datasets and findings via industry conferences, peer-reviewed journals, and relevant trade magazines, and 6) Post the resulting datasets on a publicly accessible website, which can be built on in future years. The end objective is to identify technical barriers preventing the adoption of X-ray and e-beam technologies, and share the results to encourage X-ray and e-beam adoption where feasible.

sterilization, alternate technologies, gamma, X-ra↗
DOE OSTI2020

Contrast analysis in two-beam laser interference lithography

Interference lithography enables large area, sub-µm, periodic patterning without photomasks or projection lithography tools. We show that optical contrast, which is the fundamental design variable of interference lithography, enforces coupled constraints on source coherence, beam pointing stability, field size, polarization state, and the intensity balance between beams. The analysis enables selection and alignment tolerance of components to meet a specific design requirement. In particular, the analysis reveals that grating beam splitters are significantly less sensitive to beam pointing and polarization misalignment than plate beam splitters.

Miller, David B. (ORCID:0000000207755284)↗
DOE OSTI2021

Improving probabilistic infectious disease forecasting through coherence

With an estimated $10.4 billion in medical costs and 31.4 million outpatient visits each year, influenza poses a serious burden of disease in the United States. To provide insights and advance warning into the spread of influenza, the U.S. Centers for Disease Control and Prevention (CDC) runs a challenge for forecasting weighted influenza-like illness (wILI) at the national and regional level. Many models produce independent forecasts for each geographical unit, ignoring the constraint that the national wILI is a weighted sum of regional wILI, where the weights correspond to the population size of the region. We propose a novel algorithm that transforms a set of independent forecast distributions to obey this constraint, which we refer to as probabilistically coherent. Enforcing probabilistic coherence led to an increase in forecast skill for 79% of the models we tested over multiple flu seasons, highlighting the importance of respecting the forecasting system’s geographical hierarchy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Abrolhos Bank Reef Health Evaluated by Means of Water Quality, Microbial Diversity, Benthic Cover, and Fish Biomass Data

The health of the coral reefs of the Abrolhos Bank (southwestern Atlantic) was characterized with a holistic approach using measurements of four ecosystem components: (i) inorganic and organic nutrient concentrations, [1] fish biomass, [1] macroalgal and coral cover and (iv) microbial community composition and abundance. The possible benefits of protection from fishing were particularly evaluated by comparing sites with varying levels of protection. Two reefs within the wellenforced no-take area of the National Marine Park of Abrolhos (Parcel dos Abrolhos and California) were compared with two unprotected coastal reefs (Sebastia˜o Gomes and Pedra de Leste) and one legally protected but poorly enforced coastal reef (the ‘‘paper park’’ of Timbebas Reef). The fish biomass was lower and the fleshy macroalgal cover was higher in the unprotected reefs compared with the protected areas. The unprotected and protected reefs had similar seawater chemistry. Lower vibrio CFU counts were observed in the fully protected area of California Reef. Metagenome analysis showed that the unprotected reefs had a higher abundance of archaeal and viral sequences and more bacterial pathogens, while the protected reefs had a higher abundance of genes related to photosynthesis. Similar to other reef systems in the world, there was evidence that reductions in the biomass of herbivorous fishes and the consequent increase in macroalgal cover in the Abrolhos Bank may be affecting microbial diversity and abundance. Through the integration of different types of ecological data, the present study showed that protection from fishing may lead to greater reef health. The data presented herein suggest that protected coral reefs have higher microbial diversity, with the most degraded reef (Sebastia&otilde Gomes) showing a marked reduction in microbial species richness. It is concluded that ecological conditions in unprotected reefs may promote the growth and rapid evolution of opportunistic microbial pathogens.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Inference of Causal Networks from Time-Varying Transcriptome Data via Sparse Coding

Temporal analysis of genome-wide data can provide insights into the underlying mechanism of the biological processes in two ways. First, grouping the temporal data provides a richer, more robust representation of the underlying processes that are co-regulated. The net result is a significant dimensional reduction of the genome-wide array data into a smaller set of vocabularies for bioinformatics analysis. Second, the computed set of time-course vocabularies can be interrogated for a potential causal network that can shed light on the underlying interactions. The method is coupled with an experiment for investigating responses to high doses of ionizing radiation with and without a small priming dose. From a computational perspective, inference of a causal network can rapidly become computationally intractable with the increasing number of variables. Additionally, from a bioinformatics perspective, larger networks always hinder interpretation. Therefore, our method focuses on inferring the simplest network that is computationally tractable and interpretable. The method first reduces the number of temporal variables through consensus clustering to reveal a small set of temporal templates. It then enforces simplicity in the network configuration through the sparsity constraint, which is further regularized by requiring continuity between consecutive time points. We present intermediate results for each computational step, and apply our method to a time-course transcriptome dataset for a cell line receiving a challenge dose of ionizing radiation with and without a prior priming dose. Our analyses indicate that (i) the priming dose increases the diversity of the computed templates (e.g., diversity of transcriptome signatures); thus, increasing the network complexity; (ii) as a result of the priming dose, there are a number of unique templates with delayed and oscillatory profiles; and (iii) radiation-induced stress responses are enriched through pathway and subnetwork studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

The Paris pledges and the energy-water-land nexus in Latin America: Exploring implications of greenhouse gas emission reductions

In the 2015 Paris Agreement, nations worldwide pledged emissions reductions (Nationally Determined Contributions—NDCs) to avert the threat of climate change, and agreed to periodically review these pledges to strengthen their level of ambition. Previous studies have analyzed NDCs largely in terms of their implied contribution to limit global warming, their implications on the energy sector or on mitigation costs. Nevertheless, a gap in the literature exists regarding the understanding of implications of the NDCs on countries’ Energy-Water-Land nexus resource systems. The present paper explores this angle within the regional context of Latin America by employing the Global Change Assessment Model, a state-of-the-art integrated assessment model capable of representing key system-wide interactions among nexus sectors and mitigation policies. By focusing on Brazil, Mexico, Argentina and Colombia, we stress potential implications on national level water demands depending on countries’ strategies to enforce energy-related emissions reductions and their interplays with the land sector. Despite the differential implications of the Paris pledges on each country, increased water demands for crop and biomass irrigation and for electricity generation stand out as potential trade-offs that may emerge under the NDC policy. Hence, this study underscores the need of considering a nexus resource planning framework (known as “Nexus Approach”) in the forthcoming NDCs updating cycles as a mean to contribute toward sustainable development.

Santos Da Silva, Silvia Regina↗
DOE OSTI2021

Knowledge Beacons: Web services for data harvesting of distributed biomedical knowledge

The continually expanding distributed global compendium of biomedical knowledge is diffuse, heterogeneous and huge, posing a serious challenge for biomedical researchers in knowledge harvesting: accessing, compiling, integrating and interpreting data, information and knowledge. In order to accelerate research towards effective medical treatments and optimizing health, it is critical that efficient and automated tools for identifying key research concepts and their experimentally discovered interrelationships are developed. As an activity within the feasibility phase of a project called “Translator” (https://ncats.nih.gov/translator) funded by the National Center for Advancing Translational Sciences (NCATS) to develop a biomedical science knowledge management platform, we designed a Representational State Transfer (REST) web services Application Programming Interface (API) specification, which we call a Knowledge Beacon. Knowledge Beacons provide a standardized basic API for the discovery of concepts, their relationships and associated supporting evidence from distributed online repositories of biomedical knowledge. This specification also enforces the annotation of knowledge concepts and statements to the NCATS endorsed the Biolink Model data model and semantic encoding standards (https://biolink.github.io/biolink-model/). Implementation of this API on top of diverse knowledge sources potentially enables their uniform integration behind client software which will facilitate research access and integration of biomedical knowledge.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗