Search NASA⌕ Search

SEARCH · Search NASA

Results for “Data Reporting Standards”

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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

System Study: High-Pressure Core Spray 1998-2024

This report presents an unreliability evaluation of the high-pressure core spray (HPCS) at eight U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998 to 2024 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10-year period and yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPCS results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

System Study: High-Pressure Safety Injection 1998-2024

This report presents an unreliability evaluation of the high-pressure safety injection system (HPSI) at 62 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from calendar years 1998 to 2024 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10-year period and yearly estimates for system unreliability are provided for the entire active period. Statistically significant decreasing trends were identified in both the HPSI system start-only unreliability and 24-hour mission unreliability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Systems Innovation: Modernization & Efficiencies for ESH&Q Reviews

Environmental compliance reviews at INL have traditionally been managed through fragmented systems, relying on multiple spreadsheets and manual processes. This inefficiency led to time-consuming status updates and redundant tasks, such as manually sending reminder emails and transferring data from Excel to the Environmental Review Process (ERP). Initial attempts to streamline these processes using Power Automate and Excel revealed significant limitations, necessitating a more comprehensive solution. To address these immediate inefficiencies, automated workflows were developed using Power Automate. These workflows were designed to send scheduled status update reminders and capture responses through standardized forms, with submitted data flowing directly into centralized Excel trackers. This automation reduced the administrative burden, improved data accuracy, and enabled faster, more consistent reporting. Specifically, email automation achieved a 65% efficiency gain, while data integration saw a 48% improvement, resulting in 91% of project statuses being updated within two months. Despite the improvements brought by Power Automate, the fragmented nature of the review processes persisted. To further enhance efficiency and accuracy, the Integrated Review Tool (IRT) was developed. The IRT aims to centralize review initiation and connect team systems, creating an interconnected data infrastructure that preserves team autonomy while enhancing overall efficiency. This tool automates email reminders, centralizes reviews, and streamlines data integration, significantly improving the accuracy and efficiency of environmental compliance reviews. The design and development of the IRT involved advanced systems methodology, process mapping, project management, and collaboration with subject matter experts. The minimum viable product design is 100% complete, and system development is currently underway, with expected outcomes including a centralized entry point for all ESH&Q reviews, automated routing, real-time tracking and analytics, AI integration, and a user-friendly interface. This project demonstrates the potential of leveraging automation and integrated systems to enhance efficiency, accuracy, and decision-making in environmental reporting and compliance processes at INL.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Lithium–Sulfur Batteries: 3D Printed Tools and Assembly Techniques for Repeatable Lab-Scale Coin Cell Manufacturing

The coin cell form factor has become a standard in energy storage research owing to its relatively low cost, low quantity of requisite electroactive material, fast experimental turnover, and capability to generate publishable quality data. Coin cell assembly at the lab-scale requires precise manual alignment of the many internal components of a cell to yield a properly functioning device. Truly repeatable device assembly presents a significant challenge to the acquisition of reliable data. In this report, we present a three-dimensional (3D) printable design for a coin cell alignment device and describe techniques for a generalized workflow to achieve reproducible coin cell assembly of lithium-based batteries. Standardized assembly techniques using readily accessible, purpose-built tools were demonstrated for labscale production of lithium−sulfur (Li−S) coin cells. Li−S batteries fabricated using the alignment device as well as conductive adhesive incorporated workflows afforded coin cells with up to 35% reduction of assembly times, comparable or better functional cell yields, and improved electrochemical device performance with more consistent and up to 150 mAh/g higher average discharge capacities coupled with Coulombic efficiency increases of up to 2.0% over manually aligned cell assembly techniques.

Batteries↗
DOE OSTI2022

Sister Rod Destructive Examinations (FY2021)

As a part of DOE NE High Burnup Spent Fuel Data Project, Oak Ridge National Laboratory (ORNL) is performing destructive examinations (DEs) of high burnup (HBU) (>45 GWd/MTU) spent nuclear fuel (SNF) rods from the North Anna Nuclear Power Station operated by Dominion Energy. The SNF rods, called sister rods or sibling rods, are all HBU and include four different kinds of fuel rod cladding: standard Zircaloy-4 (Zirc-4), low-tin (LT) Zirc-4, ZIRLO, and M5. This report documents the status of the ORNL Phase 1 DEs of 7 sister rods and outlines the DE tasks performed and the data collected to date, as guided by the sister rod test plans.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Sister Rod Destructive Examinations (FY22)

As a part of DOE NE High Burnup Spent Fuel Data Project, Oak Ridge National Laboratory (ORNL) is performing destructive examinations (DEs) of high burnup (HBU) (>45 GWd/MTU) spent nuclear fuel (SNF) rods from the North Anna Nuclear Power Station operated by Dominion Energy. The SNF rods, called sister rods or sibling rods, are all HBU and include four different kinds of fuel rod cladding: standard Zircaloy-4 (Zirc-4), low-tin (LT) Zirc-4, ZIRLO, and M5. This report documents the status of the ORNL Phase 1 DEs of seven sister rods and outlines the DE tasks performed and the data collected to date, as guided by the sister rod test plans.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Accelerated reliability tests of n + and p + poly-Si passivated contacts

We report on the stability of encapsulated, low-pressure chemical vapor-deposited phosphorus (n + poly-Si) doped and boron (p + poly-Si) doped poly-Si/SiO x passivated contacts by exposing the samples to three different accelerated tests: damp heat test, thermal cycling and ultraviolet exposure, adhering closely to the IEC 61215 standard. Outdoor testing was also performed by exposing the samples in the outdoor testing field at the National Renewable Energy Laboratory, and preliminary data accumulated for 1000 h from February to April of 2021 is reported. We studied non-metallized, thermally-metallized, and screen-printed n + and p + poly-Si by monitoring the effective minority carrier lifetime at the implied maximum power point using a Sinton lifetime tester, and recorded photoluminescence images before and after the exposure. Furthermore, the samples were found to be stable under all test conditions, which is encouraging for incorporation of these contacts in next-generation industrial silicon solar cells.

14 SOLAR ENERGY↗
DOE OSTI2025

A simplified approach for creep damage and remaining life calculation for materials surveillance in advanced reactors

High temperature reactor materials will experience a combination of mechanical degradation caused by creep and fatigue and environmental degradation caused by neutron irradiation and, in some cases, exposure to corrosive coolants. A materials surveillance program is one option for ensuring the safe, reliable operation of key reactor components under these conditions. Such a program would monitor the degradation in key material properties over time, using this data to predict how changes in the material properties affect components performance. This could then be used to make plant operational decisions and support eventual plant license extensions. Past work de-scribes such a material surveillance program based on passively actuated mechanical test articles that impose creep-fatigue type loading on test materials driven only by changes in temperature, for example those experienced by components under standard operating cycles. This report focuses on two aspects of the proposed material surveillance program: how to design the test articles to mimic the mechanical response of the corresponding component and how to use ex-situ test data to deter-mine the amount of damaged experienced by the test article (and hence the corresponding compo-nent) in service. Specifically, this report derives and validated simplified methods for both tasks, replacing earlier, more complicated approaches based on simulating the test article response and finding the best specimen design or current damage via complex numerical optimization. The sim-plified methods for each task developed here can be implemented in spreadsheet software and are simple enough for practical use in future operating plants. This report derives the methods (one for sizing and two options for damage inference), verifies the simplified approaches versus more so-phisticated methods, and compares the results of applying the simplified methods to previous re-sults using the complex numerical optimization approach. The report also provides a worked sam-pled problem applying the simplified techniques to a realistic high temperature reactor component.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Search for Higgs boson production in association with a high-energy photon via vector-boson fusion with decay into bottom quark pairs at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search is presented for the production of the Standard Model Higgs boson in association with a high-energy photon. With a focus on the vector-boson fusion process and the dominant Higgs boson decay into b-quark pairs, the search benefits from a large reduction of multijet background compared to more inclusive searches. Results are reported from the analysis of 132 fb –1 of pp collision data at $\sqrt{s}$ = 13 TeV collected with the ATLAS detector at the LHC. The measured Higgs boson signal yield in this final-state signature is 1.3 ± 1.0 times the Standard Model prediction. The observed significance of the Higgs boson signal above the background is 1.3 standard deviations, compared to an expected significance of 1.0 standard deviations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Mono-mix strategy enables comparative proteomics of a cross-kingdom microbial symbiosis

Cross-kingdom microbial symbioses, such as those between algae and bacteria, are key players in biogeochemical cycles. The molecular changes during initiation and establishment of symbiosis are of great interest, but quantitatively monitoring such changes can be challenging, particularly when the microorganisms differ greatly in size or are intimately associated. Here, we analyze output from label-free, data-dependent acquisition (DDA) LC-MS/MS proteomics experiments investigating the well-studied interaction between the alga Chlamydomonas reinhardtii and the heterotrophic bacterium Mesorhizobium japonicum. We found that detection of bacterial proteins decreased in coculture by 50% proteome-wide due to the abundance of algal proteins. As a result, standard differential expression analysis led to numerous false-positive reports of significantly downregulated proteins, where it was not possible to distinguish meaningful biological responses to symbiosis from artifacts of the reduced protein detection in coculture relative to monoculture. We show that data normalization alone does not eliminate the impact of altered detection on differential expression analysis of the cross-kingdom symbiosis. We assessed two additional strategies to overcome this methodological artifact inherent to DDA proteomics. In the first, we combined algal and bacterial monocultures at a relative abundance that mimicked the coculture, creating a “mono-mix” control to which the coculture could be compared. This approach enabled comparable detection of bacterial proteins in the coculture and the monoculture control. In the second strategy, we enhanced detection of lowly abundant bacterial proteins by using sample fractionation upstream of LC-MS/MS analysis. When these simple approaches were combined, they allowed for meaningful comparisons of nearly 10,000 algal proteins and over 4,000 bacterial proteins in response to symbiosis by DDA. They successfully recovered expected changes in the bacterial proteome in response to algal coculture, including upregulation of sugar-binding proteins and transporters. They also revealed novel proteomic responses to coculture that guide hypotheses about algal-bacterial interactions.

Dupuis, Sunnyjoy [University of California, Berkel↗
DOE OSTI2026

An Infrared Database of n/k Optical Constants for Calculating Aerosol Spectra for the PICARD Program

The objective of the PICARD Program is to develop fieldable sensing platforms for the rapid chemical identification of aerosol particles in plumes. Standoff detection involves interrogating the aerosol cloud from a distance using optical methods and probing the signal returned from direct backscattering from the aerosol particles or transmitted through the plume after reflection from a retroreflector or surface of opportunity (SOO). The identification of chemical species, however, in aerosols is complicated by their complex compositions and morphologies, chemical interferants, and non-uniform particle sizes. To advance standoff detection of aerosols, modelling the infrared transmittance, reflectance and scattering spectra of aerosolized liquid and solid chemical compounds is required, and then testing that model experimentally via laboratory and field experiments. To perform accurate modeling, the infrared optical constants (n/k), i.e., the complex refractive index, of the compounds of interest are required. Thus, PNNL was tasked to provide the optical constants for a set of analytes relevant to the PICARD program. This report describes the experimental techniques used to derive the optical constants of both liquid and solid compounds using established “gold-standard” protocols, how the experimental data are processed to produce the wavenumber dependent optical constant vectors, and how the data are used in the aerosol absorption spectra modeling.

complex refractive index↗
DOE OSTI2026

DOE CESER 6 GHz Interference Study

DOE CESER has sponsored Idaho National Laboratory (INL) to conduct an objective and independent study of potential 6 GHz interference from outdoor operation of unlicensed devices in the 6 GHz band on fixed service (FS) microwave communication links operated by electrical sector incumbents in that band. INL is collaborating with University of Notre Dame (UND), Electric Power Research Institute (EPRI), Lockard & White, Southern Company, and AT&T, to gather data with real-world 6 GHz interference experiments and identify (1) the potential for interference from unlicensed devices and (2) the interference necessary to cause harm to the incumbents. In addition to the functional assessment, a security assessment of the FCC mandated Automatic Frequency Coordination (AFC) System to regulate use of unlicensed 6 GHz standard power devices is also being conducted. A major objective is to create a science-based and defensible methodology used to produce the necessary data and to derive objective conclusions. This proven methodology can then be used to produce objective data and conclusions for other spectrum bands with similar incumbent uses including 4.4 – 4.9 GHz and 7.125 – 7.4 GHz, identified in the reconciliation bill that was adopted on July 4, 2025, as well as the National Spectrum Strategy discussions that are ongoing. This report contains 6 GHz field experiments and findings in the following real-world scenarios with commercial unlicensed standard power (SP) 6 GHz devices regulated by Automated Frequency Coordination (AFC): • University of Notre Dame (UND) Stadium with a capacity of 80,000 spectators, where Wi-Fi operating in 6 GHz has been deployed recently • Southern Company 6 GHz FS microwave link between Columbus and Fortson, Georgia Following are the following key findings from this study. 1. The AFC is under-protective of FS when line-of-sight exists along the path centerline. Data collected at Southern’s 6 GHz fixed link site shows significant erosion of as much as 21.4-24.4 dB of under-protection that can lead to potential service degradation under typical operating conditions. This first key finding is most likely the result of erroneous use of the RF propagation model. INL will collaborate with EPRI and the AFC Functional Requirements Working Group to submit a change request to the WinnForum TS-1014 standard towards correct use of the propagation model by the AFC. 2. There is additive interference effect of about 3 dB from nearly equal power interferers measured from simultaneous operation of two SP AP's operating co-channel with the FS receive from different locations along the path. This second key finding should be used to add the impact of additive interference of operation of multiple APs in the same geographical area, to the next generation of AFCs. INL will collaborate with FCC on the need for the AFC to consider additive interference. We also recommend that additional experiments are conducted on 6 GHz spectrum interference to further improve the AFC operation as the number of outdoor Wi-Fi devices continues to increase. These proposed steps and recommendations will make the co-existence of the incumbents and the 6 GHz outdoor Wi-Fi providers possible without any impact on the incumbents with a win-win outcome for all.

6 GHz↗
DOE OSTI2026

An improved dataset for predicting mammal infecting viruses from genetic sequence information

There have been several attempts to develop machine learning (ML) models to identify human infecting viruses from their genomic sequences, with varying degrees of success. Direct comparison between models is problematic, because these models are typically trained and evaluated on different datasets with alternative data splitting schemes, features, and model performance metrics. In this paper we present a standardized dataset of mammal infecting and non-infecting viral pathogens, refined from the previous work of Mollentze et al. to include the latest literature evidence, roughly doubling the number of curated host-virus records available to the community, and new host target labels, primate and mammal. The new host labels were included for several reasons, including previous reports that classification performance is better at broader taxonomic ranks and the idea that there may be more data for primate infection that might serve as a suitable proxy for zoonotic potential and avoidance of false positives for human infection due to absence of evidence. On this dataset, we report the performance of eight machine learning models for predicting mammal-infecting viruses from their genomic sequences. We find that randomly assigning cases in our improved dataset to training/testing sets, when compared to the original assignments into training/testing in Mollentze et al., increases the overall average ROC AUC of prediction of human infection from 0.663 ± 0.070 to 0.784 ± 0.013, consistent with the reduction in phylogenetic distance between train and test sets (relative entropy change from 3.00 to 0.08). The broadest host category of mammal infection can be predicted most reliably at 0.850 ± 0.020. We share our improved dataset and code to enable standardized comparisons of machine learning methods to predict human host infections. Overall, we have presented preliminary evidence that classification of virus host infection is more tractable at higher taxonomic ranks, that unsurprisingly reducing the phylogenetic distance between training and test sets can improve predictive performance, that peptide kmer features appear to be harmful to out of sample model performance, and we are left with the question of whether models for virus host prediction can reasonably be expected to perform well in out of sample scenarios given the likelihood that viruses do not share a common ancestor. Consistent with this concern, when the data is resampled such that there is no overlap between viral families in training and test sets (relative entropy > 24), models perform no better than random chance at prediction of human infection regardless of whether kmers are included (ROC AUC 0.50 ± 0.08) or not (ROC AUC 0.50 ± 0.04).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

ESS-DIVE Reporting Format for Dataset Package Metadata

ESS-DIVE’s (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem) dataset metadata reporting format is intended to compile information about a dataset (e.g., title, description, funding sources) that can enable reuse of data submitted to the ESS-DIVE data repository. The files contained in this dataset include instructions (dataset_metadata_guide.md and README.md) that can be used to understand the types of metadata ESS-DIVE collects. The data dictionary (dd.csv) follows ESS-DIVE’s file-level metadata reporting format and includes brief descriptions about each element of the dataset metadata reporting format. This dataset also includes a terminology crosswalk (dataset_metadata_crosswalk.csv) that shows how ESS-DIVE’s metadata reporting format maps onto other existing metadata standards and reporting formats.Data contributors to ESS-DIVE can provide this metadata by manual entry using a web form or programmatically via ESS-DIVE’s API (Application Programming Interface). A metadata template (dataset_metadata_template.docx or dataset_metadata_template.pdf) can be used to collaboratively compile metadata before providing it to ESS-DIVE.Since being incorporated into ESS-DIVE’s data submission user interface, ESS-DIVE’s dataset metadata reporting format, has enabled features like automated metadata quality checks, and dissemination of ESS-DIVE datasets onto other data platforms including Google Dataset Search and DataCite.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Repository scale classification and decomposition of tandem mass spectral data

Various studies have shown associations between molecular features and phenotypes of biological samples. These studies, however, focus on a single phenotype per study and are not applicable to repository scale metabolomics data. Here we report MetSummarizer, a method for predicting (i) the biological phenotypes of environmental and host-oriented samples, and (ii) the raw ingredient composition of complex mixtures. We show that the aggregation of various metabolomic datasets can improve the accuracy of predictions. Since these datasets have been collected using different standards at various laboratories, in order to get unbiased results it is crucial to detect and discard standard-specific features during the classification step. We further report high accuracy in prediction of the raw ingredient composition of complex foods from the Global Foodomics Project.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Powering the Blue Economy Foundational Research & Development Topics Reliability for Marine Energy Power Systems

Ocean observing platforms are deployed across the world’s oceans to collect meteorological and oceanographic data. Current technology makes use of solar panels and battery banks to provide power to these platforms, which can be challenging at high latitudes due to lack of solar insolation and cold temperatures. Marine renewable energy (MRE) generation offers a potential improvement in consistent power generation throughout the year for this use on ocean observation buoys. This report analyzes existing reliability of high latitude coastal weather buoys and tsunami detection buoys to determine performance standards that MRE generation sources must meet to become viable power sources for these remote systems. Using measurements recorded from the U.S. National Data Buoy Center’s coastal weather buoys and tsunami detection buoys, the analysis calculated the historic data availability – or the percentage of time a measurement is recorded – to evaluate the reliability of ocean observation buoys. The results show that coastal weather buoys operate at 74% data availability and the tsunami detection systems operate at an average 72% data availability. The results describe the total reliability of the system, including many different types of failures not associated with the power system such as mooring failures or equipment failures caused by extreme weather. Power system outages may only account for a small portion of the system failures. Reliability is an important design criterion for the power system of ocean observation platforms. Future power systems that would be designed for these buoys, such as an MRE generator, need to have a minimum reliability of 72% and 74% to meet the overall performance of the weather buoys and tsunami buoys, respectively. However, power system reliability likely needs to be much higher than overall system reliability, so that power system outages do not negatively impact the overall performance of the buoy.

42 ENGINEERING↗
DOE OSTI2020

CACTI Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed a large number of instruments to a region nearby the Sierra de Córdobas mountains in Argentina as part of the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign (1). During this campaign, four radars were installed at a site outside of Villa Yacanto as shown in Figure 1. As part of a post-campaign effort to improve the usability of these data, a significant activity was undertaken towards the calibration, correction, and improvement of the data quality of these radar datastreams. This process in ARM nomenclature is referred to as generating a “b1” datastream. While these “b1” standards may imply different corrections or standards for various ARM instruments, for radars it refers to a datastream that has been calibrated (and cross-calibrated), including a serious effort to deliver the highest-quality (well-characterized) data possible. This report details (i) the status/quality of the original “a1” (raw) data, (ii) the corrections and calibrations that are applied to generate these b1 datastreams, (iii) the details of the applied algorithms and how radar offset/calibration numbers were determined for the eventual corrections, and (iv) the new and flexible plug-in-based processing system designed during CACTI for radar b1 activities (current, future) that interfaces with ARM’s Data Integrator (ADI) and high-performance computing (HPC) system.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗