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NASA NTRS2019

Electra: A Modular-Based Expansion of NASA's Supercomputing Capability

NASA has increasingly relied on high-performance computing (HPC) re- sources for computational modeling, simulation, and data analysis to meet the science and engineering goals of its missions in space exploration, aeronautics, and Earth and space science. The NASA Advanced Supercomputing (NAS) Division at Ames Research Center in Silicon Valley, Calif., hosts NASA’s premier supercomputing resources, integral to achieving and enhancing the success of the agency’s missions. NAS provides a balanced environment, funded under the High-End Computing Capability (HECC) project, comprised of world-class supercomputers, including its flagship distributed-memory cluster, Pleiades; high-speed networking; and massive data storage facilities, along with multi-disciplinary support teams for user support, code porting and optimization, and large-scale data analysis and scientific visualization. However, as scientists have increased the fidelity of their simulations and engineers are conducting larger parameter-space studies, the requirements for supercomputing resources have been growing by leaps and bounds. With the facility housing the HECC systems reaching its power and cooling capacity, NAS undertook a prototype project to investigate an alternative approach for housing supercomputers. Modular supercomputing, or container-based computing, is an innovative concept for expanding NASA’s HPC capabilities. With modular supercomputing, additional containers—similar to portable storage pods—can be connected together as needed to accommodate the agency’s ever-increasing demand for computing resources. In addition, taking advantage of the local weather permits the use of cooling technologies that would additionally save energy and reduce annual water usage. The first stage of NASA’s Modular Supercomputing Facility (MSF) prototype, which resulted in a 1,000 square-foot module on a concrete pad with room for 16 compute racks, was completed in Fall 2016 and an SGI (now HPE) computer system, named Electra, was deployed there in early 2017. Cooling is performed via an evaporative system built into the module, and preliminary experience shows a Power Usage Effectiveness (PUE) measurement of 1.03. Electra achieved over a petaflop on the LINPACK benchmark, sufficient to rank number 96 on the November 2016 TOP500 list [14]. The system consists of 1,152 InfiniBand-connected Intel Xeon Broadwell-based nodes. Its users access their files on a facility-wide file system shared by all HECC compute assets via Mellanox MetroX InfiniBand extenders, which connect the Electra fabric to Lustre routers in the primary facility over fiber-optic links about 900 feet long. The MSF prototype has exceeded expectations and is serving as a blueprint for future expansions. In the remainder of this chapter, we detail how modular data center technology can be used to expand an existing compute resource. We begin by describing NASA’s requirements for supercomputing and how resources were provided prior to the integration of the Electra module-based system.

Biswas, Rupak↗

NASA NTRS2016

Virtual Flight Demonstration of the Stratospheric Dual-Aircraft Platform

A baseline configuration for the dual-aircraft platform (DAP) concept is described and evaluated in a physics-based flight dynamics simulations for two month-long missions as a communications relay in the lower stratosphere above central Florida, within 150-miles of downtown Orlando.The DAP configuration features two large glider-like (130 ft wing span) unmanned aerial vehicles connected via a long adjustable cable (total extendible length of 3000 ft) which effectively sail without propulsion using available wind shear. Use of onboard LiDAR wind profilers to forecast wind distributions are found to be necessary to enable the platform to efficiently adjust flight conditions to remain sailing by finding sufficient wind shear across the platform. The aircraft derive power from solar cells, like a conventional solar aircraft, but also extract wind power using the propeller as a turbine when there is an excess of wind shear available.Month-long atmospheric profiles (at 3-5 min intervals) in the vicinity of 60,000-ft are derived from archived data measured by the 50-Mhz Doppler Radar Wind Profiler at Cape Canaveral and used in the DAP flight simulations. A cursory evaluation of these datasets show that sufficient wind shear for DAP sailing is persistent, suggesting that DAP could potentially sail over 90% of the month-long durations even when limited by modest ascent/descent rates.DAP's novel guidance software uses a non-linear constrained optimization technique to define waypoints such that sailing mode of flight is maintained where possible, and minimal thrust is required where sailing is not practical. A set of constraints are identified which result in waypoints that enable efficient flight (i.e., minimal use of propulsion) over the two month-long flight simulations. Waypoint solutions may need to be tabulated for a wide range of potential atmospheric conditions and stored onboard for quick retrieval on a real DAP.DAP's flight control software uses an unconventional mixture of spacecraft and aircraft control techniques. Flight simulations confirms that this controls approach enables the platform to consistently reach successive waypoints over the month-long flight simulations.The ability of DAP to transition between the sailing mode (i.e., cable tension is high) and standard formation flight (i.e., cable tension is low) is a vital capability (e.g., to enable intermittent turns while stationkeeping). A new method to perform these transitions has been identified and characterized with flight simulation which requires special aircraft modifications.The energy-usage of the DAP configuration during two month-long stationkeeping missions over central Florida (i.e., stationkeeping over Orlando) is evaluated and compared to that of a pure solar aircraft of the same weight and aerodynamic performance. DAP is shown to consistently reduce net propulsion usage while simultaneously increasing solar energy capture.A baseline 700 GHz communications system is described and its performance evaluated for the proposed mission over central Florida. It is found that the variable roll orientation of the aircraft would increase the power required to maintain coverage over the stationkeeping radius of 150 miles (e.g., by as much as 100% when DAP is 150 miles from Orlando), compared to level flight. This effect can be mitigated via additional antenna design complexity or a more restricted stationkeeping radius.

Demonstrations↗

NASA NTRS2014

Processing of Packing Foams Using Heat Melt Compaction

Foam is used extensively as packing material for items sent to the International Space Station (ISS). Although lightweight, foam is bulky and can occupy a large fraction of the limited ISS volume. Four chemically distinct foams have been used on the ISS. In descending order of current usage, these are Plastazote Zotek Minicel Pyrell. Processing foam with the Heat Melt Compactor (HMC), a solid waste treatment system, has been proposed to reduce the volume of foams stored on spacecraft. Prior to HMC testing, Thermogravimetric Analyses were conducted on the four foams as a precaution to ensure that the thermal decomposition temperatures were not within range of HMC operation (180C). Pyrell was not tested with the HMC because it is known to release toxic compounds and comprises less than 1.5 of total foam usage on ISS resupply flights. Zotek, Minicel, Plastazote LD24FR (low density), and Plastazote LD45FR (high density) were processed with the HMC at 130, 150 and 170C. Volume was reduced by 82.6 on average (n19; std dev4.88). Hydrocarbons and several other compounds emitted during foam processing were measured using a Total Hydrocarbon Analyzer and FTIR. Effects of process temperature and foam type on exhaust composition are discussed. Feeding of foams into the limited size opening of the HMC compaction chamber is likely to be a challenge, particularly in microgravity. Some suggestions are proposed to facilitate feeding foam into the HMC. Processing packing foam with the HMC has been shown to substantially reduce foam volume, and also has the potential benefit of producing radiation-shielding foam tiles.

Harris, Linden↗

NASA NTRS2019

Modeling Uncertainty in Time and Fuel Benefit Estimation for TASAR Operational Evaluation

The Traffic Aware Strategic Aircrew Requests concept aims to reduce weather-induced delays, improve route efficiency, and efficiently share route modification options by combining onboard avionics data, Automatic Dependent Surveillance-Broadcast data, and broadband internet data to generate optimal, traffic-compatible trajectory changes based on real-time traffic and weather data. Time and fuel benefits due to use of the Traffic Aware Planner (TAP) software can be estimated by taking the difference in predicted flight time and fuel usage before and after a TAP-inspired trajectory change is completed. Although TAP’s optimization algorithm predicts flight and fuel usage based on the current flight route and weather data, it does not account for possible air traffic controller-initiated trajectory changes, reroutes due to sudden weather changes, or other pilot/controller actions that may occur during flight. This paper introduces an approach for quantifying the uncertainty in estimated time and fuel benefits.

Burris, Joseph↗

NASA NTRS2019

Wind Tunnel Testing of Active Flow Control on High-Lift Common Research Model

A 10%-scale high-lift version of the Common Research Model (CRM-HL) and an Active Flow Control (AFC) version of the model equipped with a simple-hinged flap (CRM-SHLAFC) were successfully tested. The tests were performed in the 14- by 22-Foot Subsonic Tunnel (14x22) at the NASA Langley Research Center (LaRC). The CRM-HL has a set of 37° inboard and outboard single-element Fowler flaps. The CRM-SHL-AFC has a set of 50° inboard and 55° outboard simple-hinged flaps equipped with integrated modular AFC cartridges on the flap shoulder. Both high-lift configurations share the same 30° slats and engine nacelle. Three new types of AFC devices were examined: the Double-Row Sweeping Jets (DRSWJ), the Alternating Pulsed Jets (APJ), and the High Efficiency Low Power (HELP) actuators. The DRSWJ and the APJ actuators used two rows of unsteady jets, whereas the HELP actuators used a combination of unsteady and steady jets, to overcome strong adverse pressure gradients while minimizing the mass flow usage. Nozzle pressure ratio, mass flow consumption and the power coefficient, which takes account of both supply air pressure and mass flow usage for the actuators, were used for judging the performance efficiency of the AFC devices. A prestall lift performance degradation for the CRM-HL configuration was resolved with a properly placed nacelle chine. The configuration with nacelle chine was chosen as the representative reference conventional high-lift case for comparison with the CRMSHL- AFC. The AFC-induced lift coefficient increment (DCL) was maintained for the entire lift curve over the CRM-SHL-AFC case with no AFC for almost all flow-control cases examined. The lift curve of the reference CRM-HL have a slightly steeper slope compared to those of the CRM-SHL-AFC configurations. The HELP actuation concept was extremely effective in controlling flow separation in the “linear region” of the curves comparing lift coefficient to mass flow rate. The HELP actuation achieved a targeted DCL of 0.50 using a moderate amount of mass flow and supply air pressure. The CRM-SHL-AFC configuration equipped with HELP actuation was able to match or exceed the lift performance of the reference conventional high-lift configuration (i.e., CRM-HL equipped with a nacelle chine), thus meeting the NASA Advanced Air Transport Technology (AATT) project goal.

Lin, John C.↗

NASA NTRS2020

Wind Tunnel Testing of High Efficiency Low Power (HELP) Actuation for Active Flow Control

A High Efficiency Low Power (HELP) methodology has been successfully developed and tested on an active flow control (AFC) version of the 10%-scale high-lift Common Research Model (CRM-HL) at the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel (14x22). The AFC variant of the CRM-HL, designated as CRM-SHL-AFC, was integrated with modular HELP actuator cartridges on the shoulder of its highly deflected (≥50°) simplehinged flaps. A reference conventional CRM-HL configuration equipped with Fowler flaps and a nacelle chine was chosen to provide the targeted lift enhancement goals and for comparison with the results of the CRM-SHL-AFC. The current data are presented with the Transonic Wall Interference Correction System (TWICS) method applied. The HELP actuators, which use a combination of unsteady sweeping jets and steady discrete jets in tandem, were designed to overcome strong adverse pressure gradients, while minimizing the pneumatic power usage. The power coefficient (C(sub π)), which takes account of both supply air pressure and mass flow usage for the AFC actuators, is a useful parameter for judging the actuators’ performance efficiency and perhaps for scaling-up of the AFC system. Full HELP actuation coverage with a constant spanwise nozzle pressure ratio (NPR) was able to achieve the lift enhancement goals for the entire lift curve and was found to be the most effective AFC case. For the most effective case, mass flow rates greater than ~0.91 lbm/s and NPR values greater than ~1.8 (corresponding to C(sub π) = 0.18) are needed to achieve the lift enhancement goal at α = 9°, whereas mass flow rates greater than ~1.23 lbm/s and NPR values greater than ~2.3 (corresponding to C(sub π) = 0.3) are needed to achieve the lift enhancement goal at α = 17°. Surface pressure distributions indicate that the HELP actuation on the flap shoulder increased the suction pressures (and flow circulation) globally in both the streamwise and the spanwise directions, and thereby enhanced the lift over the entire high-lift system. The CRM-SHLAFC configuration equipped with HELP actuation was able to match or exceed the lift performance of the reference conventional CRM-HL, thus meeting the objective of the research.

John C Lin↗

NASA NTRSDate not supplied

More / All Electric Vertical Take-Off and Landing (VTOL) Vehicle Sensitivities to Propulsion and Power Performance

Battery power and energy density are important parameters for the emerging concepts for more / all-electric vehicles. Electric propulsion and power system performance is also important. To better understand how electric propulsion and power systems component performance influences overall vehicle design, a sensitivity assessment was performed noting changes in vehicle gross weight and energy usage. Updated versions of the Revolutionary Vertical lift Technology (RVLT) Project vertical take-off and landing (VTOL) urban air mobility (UAM) reference vehicles and missions were used. NASA electric vehicle studies are discussed which were used to help select the range of electric propulsion and power system performance parameters used in this assessment. Thermal management systems (TMS) considerations are also important; new and innovative power management and distribution systems can reduce electric system weight and losses, reducing thermal management constraints often imposed by electric systems modest maximum use temperatures. Vehicles with higher disk loadings (smaller rotors) require higher power levels per unit weight for VTOL operations, which make them more sensitive to electric system weights and efficiencies. Battery, all-electric vehicles show different sensitivities to component performance than turboelectric or hybrids systems. Battery, all-electric propulsion systems may increase vehicle weight and size, but still results in lower mission energy usage than their hydrocarbon-fueled versions. Significant vehicle weight growth to electric propulsion and power system power-to-weight reductions also occurs at different levels among the various concepts. From these results, one can more readily identify required component performance levels, potential component choices or, research and development paths.

Electric Propulsion Systems (Aircraft)↗

NASA NTRSDate not supplied

More / All Electric Vertical Take-Off and Landing (VTOL) Vehicle Sensitivities to Propulsion and Power Performance

electric propulsion systems (aircraft) mission ana↗

NASA NTRS2020

Electrical Modeling and Thermal Analysis Toolbox (EMTAT) User’s Guide

A simulation toolbox has been developed to model the electrical portions of Electrified Aircraft Propulsion (EAP) systems, including self-heating of electrical systems. Dynamic models of EAP systems often include turbomachinery, an electrical power system, and a thermal management system. These portions of the propulsion system can operate on timescales covering six orders of magnitude, which poses a challenging modeling task. Assumptions and approximations are made in an effort to capture the dynamics relevant to engine, electrical system, and thermal system interactions, while still allowing for fast simulations. These assumptions and approximations enable the electrical component models to run at the time scale of the turbomachinery, neglecting the very high frequency electrical dynamics, while demonstrating representative behavior of the end-to-end system. Thus the models execute in an acceptable time frame for what would otherwise be an extremely stiff simulation. The resulting simulations of EAP systems are appropriate for system-level control design and analysis. The objective of this User's Guide is to present an overview of the usage of the Electrical Modeling and Thermal Analysis Toolbox (EMTAT). It will describe some of the approximations made to accommodate rapid execution, and some of the design tools that allow matching the model to component specifications. This paper will describe the basic usage of the software toolbox, and also provide an example of EAP system modeling using EMTAT.

Mark E. Bell↗

NASA NTRSDate not supplied

"Giovanni at 20: Consistency and Persistency in Making Earth Remote Sensing Data Available (and Useful) to the Earth Science Community"

Since its creation in the year 2000, the NASA Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) has been an exemplar of how to provide remotely-sensed satellite data and related Earth science datasets to a broad and globally diverse researcher community. One of the hallmarks of Giovanni system usage is that it is common to see practitioners of many branches of science – particularly those in fields not traditionally associated with remote-sensing data, such as animal behavior and paleooceanography – both accessing and employing datasets which the system provides. This usage pattern is attested to by the diversity of published science citing Giovanni. Giovanni has evolved through several versions, each of which increased analytical and visualization options while also enhancing ease-of-use. Information resources supporting Giovanni from the Goddard Earth Sciences Data and Information Services Center (GES DISC), which hosts the system, start with basic mapping and plotting functions and extend to “How-to” recipes demonstrating interusability with other data analysis systems and software. Giovanni is now being developed for use in a cloud environment, potentially expanding datasets the system can be applied to, and also improving performance for data having high spatial and temporal resolution. This presentation covers the system’s historical success with interesting examples of Giovanni-citing research, and will apply its current capabilities to a multi-dataset examination of derecho events associated with mesoscale convective phenomena in the summer of 2020, indicating how Giovanni is prepared for ongoing support of Earth science in a changing world.

Giovanni Derecho visualization↗

NASA NTRSDate not supplied

Exploring Transfers Between Earth-Moon Halo Orbits via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization, a multi-objective deep reinforcement learning algorithm, is used to examine the design space of low-thrust trajectories for a SmallSat transferring between two libration point orbits in the Earth-Moon system. Using Multi-Reward Proximal Policy Optimization, multiple policies are simultaneously and efficiently trained on three distinct trajectory design scenarios. Each policy is trained to create a unique control scheme based on the trajectory design scenario and assigned reward function: a unique combination of weights scaling competing objectives that guide the spacecraft to the target mission orbit, incentivize faster flight times, and penalize propellant mass usage. Then, the policies are evaluated on the same set of perturbed initial conditions in each scenario to generate the propellant mass usages, flight times, and state discontinuities from a reference trajectory for each control scheme. This solution space of low-thrust trajectories for a SmallSat is used to examine the multi-objective trade space for the trajectory design scenario. By autonomously constructing the solution space, insights into the required propellant mass, flight time, and transfer geometry are rapidly achieved.

Christopher J Sullivan↗

NASA NTRSDate not supplied

Impact of Handling Qualities on Motor Sizing for Multirotor Aircraft with Urban Air Mobility Missions

Control models of three NASA Urban Air Mobility (UAM) reference vehicles (the quadrotor, octocopter, and Lift+Cruise (LPC)) were created and compared to determine the effect of rotor number and disk loading on control margin and design. The heave and yaw axes demand more actuator usage than the roll and pitch axes. Between heave and yaw, heave was the more demanding of the two because of the dependence of heave on the engine speed controller (ESC). When the feedback gains for all three vehicles were optimized to Level 1 handling qualities (HQs) specifications using CONDUIT, the ESC for the octocopter was the most stable and had the highest rise time (time for the rotor to respond to an input), while the LPC ESC was the least stable and had the smallest rise time. Rise time corresponds to the time required for rotor response. When actuator usage was translated to current margin, torque margin, and power margin, heave was the most demanding axis, followed by yaw, roll, and then pitch for all three vehicles. The results emphasize the importance of an accurate motor model within the control system architecture.

Impact↗

NASA NTRSDate not supplied

Trend Analysis of AI/ML Tools and Services in NASA

Usage of Machine Learning (ML) algorithms within NASA’s Science Mission Directorates have been increasing over the years. This can be quantitatively observed in the upward trends of ML usage found by analyzing the publications and presentations (in affiliation with NASA) available through NASA Technical Reports Server (NTRS) and PubMed Central(PMC). Identifying the problem types and class of ML algorithms used to tackle them across the divisions can present opportunities for collaborations, interdisciplinary projects and knowledge transfer for sustainable partnerships. In this presentation, we will present the trend analysis of ML algorithms used in different SMD divisions based on the publications and presentations publicly available. We identify these trends by leveraging ML algorithms which are able to search through the publication texts semantically; which are also highly scalable. We will also present an analysis on the available opensource tools and services in NASA leveraging AI/ML algorithms. This work will provide ample avenues for collaborative efforts across different disciplines based on the surfaced trends.

Slesa Adhikari↗

NASA NTRSDate not supplied

Trend Analysis of AI/ML Tools and Services in NASA

Usage of Machine Learning (ML) algorithms within NASA’s Science Mission Directorates have been increasing over theyears. This can be quantitatively observed in the upward trends of ML usage found by analyzing the publications andpresentations (in affiliation with NASA) available through NASA Technical Reports Server (NTRS) and PubMed Central(PMC). Identifying the problem types and class of ML algorithms used to tackle them across the divisions can presentopportunities for collaborations, interdisciplinary projects and knowledge transfer for sustainable partnerships. In thispresentation, we will present the trend analysis of ML algorithms used in different SMD divisions based on the publicationsand presentations publicly available. We identify these trends by leveraging ML algorithms which are able to search throughthe publication texts semantically; which are also highly scalable. We will also present an analysis on the available opensource tools and services in NASA leveraging AI/ML algorithms. This work will provide ample avenues for collaborativeefforts across different disciplines based on the surfaced trends.

Slesa Adhikari↗

NASA NTRS2020

2020 IEEE Paper on Psyche margin management, Draft

In January 2017, the mission concept Psyche: Journey to a Metal World was one of two concepts selected by NASA for implementation as part of the 14th Discovery mission competition. Over the course of the past year, the Psyche team has actively worked to refine and mature the technical design, culminating in a successful completion of the Project Preliminary Design review and approval to proceed to Phase C in mid-2019. Psyche is a deep space mission utilizing solar electric propulsion (SEP), consisting of SPT-140 Hall thrusters which have been successfully employed on multiple commercial spacecraft. When launched, Psyche will carry over 1000 kg of Xenon, and will represent the farthest usage of electric propulsion usage from the Sun – a distance of over 3.3 AU. The use of solar electric propulsion in deep space has resulted in challenges unique to other missions. Spacecraft designs typically balance margins across two main elements – mass and power – that are independent of one another. Utilizing a low thrust trajectory through the application of electric propulsion introduces more elements - namely flight time, missed thrust percentage and thruster duty cycle. Moreover, these elements become connected, presenting additional relationships that must be considered. This paper will present an overview of the margin management process for Psyche, and how it has evolved from the early proposal stage to its current state. It will discuss the elements that are margined, their relationship with one another, and key uncertainties that must be addressed. It discusses challenges and mitigations obtained during the refinement of the Psyche project, culminating in a new margin strategy that enables optimization across many of the system elements, and will serve as a template for future deep space SEP missions.

Hart, William↗

NASA NTRS2021

Exploring Transfers Between Earth-Moon Halo Orbits via Multi-Objective Reinforcement Learning

Multi-Reward Proximal Policy Optimization, a multi-objective deep reinforcement learning algorithm, is used to examine the design space of low-thrust trajectories for a SmallSat transferring between two libration point orbits in the Earth- Moon system. Using Multi-Reward Proximal Policy Optimiza- tion, multiple policies are simultaneously and efficiently trained on three distinct trajectory design scenarios. Each policy is trained to create a unique control scheme based on the trajectory design scenario and assigned reward function: a unique combination of weights scaling competing objectives that guide the spacecraft to the target mission orbit, incentivize faster flight times, and penalize propellant mass usage. Then, the policies are evaluated on the same set of perturbed initial conditions in each scenario to generate the propellant mass usages, flight times, and state discontinuities from a reference trajectory for each control scheme. This solution space of low-thrust trajectories for a SmallSat is used to examine the multi-objective trade space for the trajectory design scenario. By autonomously constructing the solution space, insights into the required propellant mass, flight time, and transfer geometry are rapidly achieved.

Mashiku, Alinda K.↗

NASA NTRSDate not supplied

Robust Trajectory Optimization for Guided Powered Descent and Landing

A robust trajectory optimization approach for guidance algorithm gain selection for powered descent and landing is developed. This approach uses a genetic algorithm to determine optimal guidance algorithm parameters while incorporating uncertainty information from linear covariance analysis. The optimal guidance algorithm parameters are determined while accounting for environment, navigation, and vehicle property uncertainty and sensor suite fidelity. As a demonstration of this method, the optimal gains for the fractional polynomial powered descent guidance are found for the braking phase of a robotic lunar landing mission. Scenarios with differing sensor suites and sensor qualities are considered, with objective functions to minimize variability in propellant usage or terminal position. Results show that the optimal guidance algorithm gains for a given trajectory differ based on the sensor suite, and optimal guidance algorithm gains may result in up to 20% performance improvements over the baseline in propellant usage and landed accuracy.

Grace E Calkins↗

NASA NTRSDate not supplied

Scaling a Smart Sub-metered Electrical Data Solution for the Center

Currently, there is no single Center-level point solution that enables facility systems data to be collected and stored from buildings on-site, on-demand, and through a faceted search capability that would enable the cultivation of deeper insights into incipient facility-related issues that would otherwise be overlooked. Such insights would represent a powerful and very valuable tool to aid in data-driven decision making and informing actionable steps for remediation and resolution of these problems. Access to electrically sub-metered data via hardware upgrades is in the process of being restored for Building N232, Sustainability Base, but this is only the first step. The native software capabilities that were originally part of a proposed Agencywide Smart Center initiative project can unlock the ability to access actionable insights. This work would also nicely complement many initiatives that are actively being pursued, under consideration, or pending submission to this same call at the Center. This project is poised to support an NRSAA with Verdigris Technologies, as well as in support of an Agencywide Smart Center initiative. Monitoring electrical consumption usage at the most granular level in Bldg. N232 will be instrumental in accurately quantifying potential utility costs and investments, and monitoring usage trends, as it is being converted into hoteling spaces, to help. This will also help with determining how the capability can scale more broadly across the Center and Agency at large.

Rodney Alexander Martin↗