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All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Parallelization and Visual Analysis of Multidimensional Fields: Application to Ozone Production, Destruction, and Transport in Three Dimensions

The three-dimensional, spectral transport model used in the current project was first successfully integrated over climatological time scales by Dr. Guang Ping Lou for the simulation of atmospheric N2O using the United Kingdom Meteorological Office (UKMO) 4-dimensional, assimilated wind and temperature data set. A non-parallel, FORTRAN version of this integration using a fairly simple N2O chemistry package containing only photo-chemical reactions was used to verify our initial parallel model results. The integrations reproduced the gross features of the observed stratospheric climatological N2O distributions but also simulated the structure of the stratospheric Antarctic vortex and its evolution. Subsequently, Dr. Thomas Kindler, who produced much of the parallel version of our model, enlarged the N2O model chemistry package to include N2O reactions involving O(D-1) and also introduced assimilated wind data from NASA as well as UKMO. Initially, transport calculations without chemistry were run using Carbon-14 as a non-reactive tracer gas with the result that large differences in the transport properties of the two assimilated wind data sets were apparent from the resultant Carbon-14 distributions. Subsequent calculations for N2O, including its chemistry, with the two input winds data sets with verification from UARS satellite observations have refined the transport differences between the two such that the model's steering capabilities could be used to infer the correct climatological vertical velocity fields required to support the N2O observations. During this process, it was also discovered that both the NASA and the UKMO data contained spurious values in some of the higher frequency wave components, leading to incorrect local transport calculations and ultimately affecting the large scale properties of the model's N2O distributions, particularly at tropical latitudes. Subsequent model runs with wind data that had been filtered to remove some of the high frequency components produced much more realistic N2O distributions. During the past few months, the UKMO wind data base for a complete two-year period was processed into spectral form for model use. This new version of the input transport data base now includes complete temperature fields as well as the necessary wind data. This was done to facilitate advanced chemical calculations in the parallel model which often depend upon temperature. Additional UKMO data is being added as it becomes available.

Schwan, Karsten↗
NASA NTRSDate not supplied

Construction of a Fluid Flowfield from Discrete Point Data using Machine Learning

Many verification and validation procedures in aerospace engineering involve the comparison of computational fluid dynamics (CFD) data to experimental results from sources like wind tunnel tests. However, an incongruity exists between the data available from these sources: flow visualization is available by default in computational data, whereas in most experimental setups the available data is far more discrete and far more limited: integrated forces and moments, discrete pressure and temperature probes, etc. When differences exist between quantities of interest like lift and drag coefficients, the lack of full-field flow data from the experiments complicates most attempts to reconcile why the different data sources disagree. To this end, a shallow neural network, constrained by certain fluid flow properties, was trained to approximate flow field snapshots given only discrete data like that available in a wind tunnel test. The constructed snapshots, even for complex incompressible fluid flows, were found to agree at the large scales with the true flow fields. With this tool, researchers can more readily and easily understand why quantities of interest differ between their experimental and computational datasets. This in turn improves the resulting data's uncertainty measures.

Yury Lebedev↗
NASA NTRSDate not supplied

Construction of a Fluid Flowfield from Discrete Point Data using Machine Learning

Many verification and validation procedures in aerospace engineering involve the comparison of computational fluid dynamics (CFD) data to experimental results from sources like wind tunnel tests. However, an incongruity exists between the data available from these sources: flow visualization is available by default in computational data, whereas in most experimental setups the available data is far more discrete and far more limited: integrated forces and moments, discrete pressure and temperature probes, etc. When differences exist between quantities of interest like lift and drag coefficients, the lack of full-field flow data from the experiments complicates most attempts to reconcile why the different data sources disagree. To this end, a shallow neural network, constrained by certain fluid flow properties, was trained to approximate flow field snapshots given only discrete data like that available in a wind tunnel test. The constructed snapshots, even for complex incompressible fluid flows, were found to agree at the large scales with the true flow fields. With this tool, researchers can more readily and easily understand why quantities of interest differ between their experimental and computational datasets. This in turn improves the resulting data's uncertainty measures.

Yury Lebedev↗
NASA NTRS1972

Space Shuttle bipropellant RCS engine.

The requirements of the Space Shuttle bipropellant reaction control system engine technology contract and the scheduled contract effort are presented herein. The requirements included an engine concept scalable from 400 to 1100 lbf, with a 100 mission life employing N2O4/MMH propellants. Emphasis is placed on reusability and minimum post-flight servicing. The engine components are reviewed and their selection is supported by tradeoff analyses, thrust chamber firing test data, materials test data, and metallurgical evaluations. The materials test data indicate that the proposed silicide coated columbium chamber and uncoated columbium injector have the potential of meeting the mission life requirements. The engine valve trade studies resulted in the selection of a torque motor operated bipropellant valve configuration. Fuel vortex film cooling of the insulated chamber is described together with the fuel vortex film cooling scaling parameter and its verification by test data to a thrust level of 5500 lbf.

Sanscrainte, W.↗
NASA NTRS2021

Chapter 6: Fundamental Satellite Precipitation Data Records

The observation and measurement of precipitation across a range of temporal and spatial scales is of great importance for many user requirements and applications. Precipitation is a key component of the global energy and water cycle moving water, and its’ associated energy, through the Earth system at relatively fine spatial and temporal scales. At the societal level, precipitation provides fresh water and moderates our climate, but can also be destructive through storms, droughts and spreading diseases. Monitoring and measuring the distribution and quantities of precipitation, across the Earth’s surface is therefore crucial to physical and social applications, together with changes in precipitation over time. While conventional surface instruments provide a reasonably long record, these tend to be confined to well populated land surface areas: most ocean regions and sparsely populated regions have few measurements. Satellite-based precipitation products can provide global measurements, although the timespan of such products is limited and the data record is comprised of different instruments that operate over different periods of record. The challenge of any climate record is to provide a consistent product over the full period of record. Many satellite precipitation products incorporate ancillary data, such as surface gauge data or model data, which may limit their utility in the validation or verification of other climate data records. This chapter provides a review of the importance of precipitation to the climate system, the basis of satellite precipitation retrievals, climate data records of satellite data for precipitation retrievals and the development of fundamental precipitation data records for climate applications.

Climate data record↗
DOE OSTI2020

A secure measurement unit for an inspection system used in nuclear arms-control verification

Verification of arms control treaties may require information barriers to protect sensitive data acquired during the verification process. These information barriers are commonly implemented in software, but must store and operate on data that are vulnerable to attack and tampering. Here, we present a new Secure Measurement Unit based on a modified pipeline SAR ADC architecture. The idea is to move the information barrier back into the digitization process so that prohibited data is never created. A prototype 65nm CMOS Secure Measurement Unit (SMU) was tested using U-235, U-238, Co-60, Cs-137 and Am-241 sources. Here, the prototype accurately digitized allowable signals while being immune to side-channel attacks on signals within preset forbidden regions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2010

Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

This paper presents a detailed convective forecast accuracy analysis at center and sector levels. The study is aimed to provide more meaningful forecast verification measures to aviation community, as well as to obtain useful information leading to the improvements in the weather translation capacity models. In general, the vast majority of forecast verification efforts over past decades have been on the calculation of traditional standard verification measure scores over forecast and observation data analyses onto grids. These verification measures based on the binary classification have been applied in quality assurance of weather forecast products at the national level for many years. Our research focuses on the forecast at the center and sector levels. We calculate the standard forecast verification measure scores for en-route air traffic centers and sectors first, followed by conducting the forecast validation analysis and related verification measures for weather intensities and locations at centers and sectors levels. An approach to improve the prediction of sector weather coverage by multiple sector forecasts is then developed. The weather severe intensity assessment was carried out by using the correlations between forecast and actual weather observation airspace coverage. The weather forecast accuracy on horizontal location was assessed by examining the forecast errors. The improvement in prediction of weather coverage was determined by the correlation between actual sector weather coverage and prediction. observed and forecasted Convective Weather Avoidance Model (CWAM) data collected from June to September in 2007. CWAM zero-minute forecast data with aircraft avoidance probability of 60% and 80% are used as the actual weather observation. All forecast measurements are based on 30-minute, 60- minute, 90-minute, and 120-minute forecasts with the same avoidance probabilities. The forecast accuracy analysis for times under one-hour showed that the errors in intensity and location for center forecast are relatively low. For example, 1-hour forecast intensity and horizontal location errors for ZDC center were about 0.12 and 0.13. However, the correlation between sector 1-hour forecast and actual weather coverage was weak, for sector ZDC32, about 32% of the total variation of observation weather intensity was unexplained by forecast; the sector horizontal location error was about 0.10. The paper also introduces an approach to estimate the sector three-dimensional actual weather coverage by using multiple sector forecasts, which turned out to produce better predictions. Using Multiple Linear Regression (MLR) model for this approach, the correlations between actual observation and the multiple sector forecast model prediction improved by several percents at 95% confidence level in comparison with single sector forecast.

Wang, Yao↗
NASA NTRS2015

Using Empirical Models for Communication Prediction of Spacecraft

A viable communication path to a spacecraft is vital for its successful operation. For human spaceflight, a reliable and predictable communication link between the spacecraft and the ground is essential not only for the safety of the vehicle and the success of the mission, but for the safety of the humans on board as well. However, analytical models of these communication links are challenged by unique characteristics of space and the vehicle itself. For example, effects of radio frequency during high energy solar events while traveling through a solar array of a spacecraft can be difficult to model, and thus to predict. This presentation covers the use of empirical methods of communication link predictions, using the International Space Station (ISS) and its associated historical data as the verification platform and test bed. These empirical methods can then be incorporated into communication prediction and automation tools for the ISS in order to better understand the quality of the communication path given a myriad of variables, including solar array positions, line of site to satellites, position of the sun, and other dynamic structures on the outside of the ISS. The image on the left below show the current analytical model of one of the communication systems on the ISS. The image on the right shows a rudimentary empirical model of the same system based on historical archived data from the ISS.

Quasny, Todd↗
NASA NTRS2023

Exploration Medical Capability IMPACT Medical Database – Medical Item Database (MedID) Content Development Methods

The Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) project encompasses a suite of computational tools that are used to inform systematic trade study evaluations and research prioritizations regarding the optimization of spaceflight medical systems, including the provision of risk assessment metrics, for a given design reference mission (DRM). The IMPACT Medical Database (IMPACT-MD) is the component that virtually houses the clinical and engineering data for medical conditions, capabilities, and resources used to support these analyses. In addition, IMPACT-MD also provides data to the associated SysML model to support the Level 2, Level 3, and Level 4 requirements development needed for IMPACT. IMPACT-MD contains an internal Evidence Library (EL) sub-component that hosts the clinical evidence, treatment and outcome metric data, and incidence data for each medical condition identified for exploration-class missions. Furthermore, a separate Medical Item Database (MedID) sub-component hosts the engineering data and physical attributes (e.g., mass, volume, power, etc.) associated with each medical resource item identified to address the requisite medical conditions. The IMPACT project is conducted under the Exploration Medical Capability (ExMC) element of the Human Research Program (HRP) within NASA's Space Operations Mission Directorate (SOMD). The reader is referred to the documents in Appendix A for a more complete overview of the IMPACT tool suite and functionality as well as further detail on any associated aspects of the project. The primary purpose of this document is to describe the methods utilized in the collection and verification of engineering data content during the project development phase for the MedID sub-component of the IMPACT-MD project. Engineering content data (both existing and new/future) will be stored in IMPACT-MD for use by the IMPACT project. This document will detail the content development and data credibility for the engineering data housed within the MedID subcomponent of IMPACT-MD, which is used to inform the IMPACT 1.0 project deliverables.

Exploration Medical Capability↗
NASA NTRS2010

Community-Based Services that Facilitate Interoperability and Intercomparison of Precipitation Datasets from Multiple Sources

Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.

Liu, Zhong↗
NASA NTRS2011

Space Shuttle Day-of-Launch Trajectory Design Operations

A top priority of any launch vehicle is to insert as much mass into the desired orbit as possible. This requirement must be traded against vehicle capability in terms of dynamic control, thermal constraints, and structural margins. The vehicle is certified to specific structural limits which will yield certain performance characteristics of mass to orbit. Some limits cannot be certified generically and must be checked with each mission design. The most sensitive limits require an assessment on the day-of-launch. To further minimize vehicle loads while maximizing vehicle performance, a day-of-launch trajectory can be designed. This design is optimized according to that day s wind and atmospheric conditions, which increase the probability of launch. The day-of-launch trajectory design and verification process is critical to the vehicle s safety. The Day-Of-Launch I-Load Update (DOLILU) is the process by which the National Aeronautics and Space Administration's (NASA) Space Shuttle Program tailors the vehicle steering commands to fit that day s environmental conditions and then rigorously verifies the integrated vehicle trajectory s loads, controls, and performance. This process has been successfully used for almost twenty years and shares many of the same elements with other launch vehicles that execute a day-of-launch trajectory design or day-of-launch trajectory verification. Weather balloon data is gathered at the launch site and transmitted to the Johnson Space Center s Mission Control. The vehicle s first stage trajectory is then adjusted to the measured wind and atmosphere data. The resultant trajectory must satisfy loads and controls constraints. Additionally, these assessments statistically protect for non-observed dispersions. One such dispersion is the change in the wind from the last measured balloon to launch time. This process is started in the hours before launch and is repeated several times as the launch count proceeds. Should the trajectory design not meet all constraint criteria, Shuttle would be No-Go for launch. This Shuttle methodology is very similar to other unmanned launch vehicles. By extension, this method would likely be employed for any future NASA launch vehicle. This paper will review the Shuttle s day-of-launch trajectory optimization and verification operations as an example of a more generic application of day-of-launch design and validation. With Shuttle s retirement, it is fitting to document the current state of this critical process and capture lessons learned to benefit current and future launch vehicle endeavors.

Harrington, Brian E.↗
NASA NTRS2008

The Solid Rocket Motor Slag Population: Results of a Radar-Based Regressive Statistical Evaluation

Solid rocket motor (SRM) slag has been identified as a potential source of man-made orbital debris. The possibility that SRMs (in addition to generating dust particles in the sub-millimeter range) may generate particles up to centimeters in size has caused concern regarding their contribution to the debris environment. Returned surfaces from space do not have sufficient area or exposure time to provide a clear picture of the SRM millimeter and centimeter debris population. Currently, radar observation is probably the only way to collect data showing the debris contribution from SRMs. Such observation is used to sample the debris environment, but it is difficult to obtain accurate orbital elements for the detected debris objects. NASA has developed several models to describe the different orbital debris populations, based on assumed debris production mechanisms to create clouds of debris objects that can be propagated in time. The NASA model, LEGEND (LEO-to-GEO Environment Debris), functions as a time-tested debris model for most debris sources. However, the current LEGEND model does not include contributions from the SRM population. An SRM model has recently been developed by NASA, based on purely theoretical details of SRM production and known SRM launches, but verification with hard data is needed. Because the detections of individual SRM objects cannot be deterministically separated from the total debris observed by radar, the validation of the SRM model can only be done by combining it with the LEGEND breakup model and comparing it with data. By applying observational constraints, the degree of SRM slag contribution to the environment may be estimated. This serves as an observationally sound method from which to calibrate a purely theoretical model into something more realistic. For this study, we use the populations observed by the Haystack radar from 1996 to present. For the SRM debris, we use a historical database of SRM launches, propellant masses, and estimated locations and times of tailoff to produce and propagate the SRM debris clouds. Comparisons with radar data from the ensuing years were made, and the SRM model was altered with respect to size and mass production of slag particles to reflect the populations estimated from the data. The result is a model SRM population that fits within the bounds of the observed environment and estimates of the production and contribution of SRM debris to the environment.

Horstman, Matthew F.↗
NASA NTRS2006

Impact Damage and Strain Rate Effects for Toughened Epoxy Composite Structures

Structural integrity of composite systems under dynamic impact loading is investigated herein. The GENOA virtual testing software environment is used to implement the effects of dynamic loading on fracture progression and damage tolerance. Combinations of graphite and glass fibers with a toughened epoxy matrix are investigated. The effect of a ceramic coating for the absorption of impact energy is also included. Impact and post impact simulations include verification and prediction of (1) Load and Impact Energy, (2) Impact Damage Size, (3) Maximum Impact Peak Load, (4) Residual Strength, (5) Maximum Displacement, (6) Contribution of Failure Modes to Failure Mechanisms, (7) Prediction of Impact Load Versus Time, and (8) Damage, and Fracture Pattern. A computer model is utilized for the assessment of structural response, progressive fracture, and defect/damage tolerance characteristics. Results show the damage progression sequence and the changes in the structural response characteristics due to dynamic impact. The fundamental premise of computational simulation is that the complete evaluation of composite fracture requires an assessment of ply and subply level damage/fracture processes as the structure is subjected to loads. Simulation results for the graphite/epoxy composite were compared with the impact and tension failure test data, correlation and verification was obtained that included: (1) impact energy, (2) damage size, (3) maximum impact peak load, (4) residual strength, (5) maximum displacement, and (6) failure mechanisms of the composite structure.

Chamis, Christos C.↗
NASA NTRS1984

Magnetospheric ions and electrons in the distant magnetosheath at about 50 and 180 earth radii - ISEE-3 observations

Energetic particle data were obtained in the dawn magnetosheath at about 50 earth radii (ER), analyzed, and compared with data taken at 180 ER. Both data sets were acquired during the ISEE-3 geotail mission. The results of analyses of the 16 sec time profiles of 32 and 130 keV protons, 75-115 keV electrons, and some of the 30-36 keV proton angular distributions (PAD) are presented. No temporal dispersions were detected in the particle bursts, implying instead a spatial dispersion. The particles filled flux tubes of 6 ER, with the energetic electrons being beamed along magnetic field lines. PADs displayed anisotropy symmetric relative to the magnetic field. The electrons were not detected at 180 ER. The phenomena are modeled as flux tubes connected to the magnetotail magnetic field in the near-earth magnetopause. The particles leak out along connected field lines. Lion roars scatter the electrons, which escape into interplanetary space. Ions, however, may carry their intensity out to 200 ER, a factor which awaits verification by further data.

Scholer, M.↗
NASA NTRS1995

Aerodynamic Evaluation of Two Compact Radial-Inflow Turbine Rotors

The aerodynamic evaluation of two highly loaded compact radial turbine rotors was conducted at the NASA Lewis Research Center Small Engine Component Test Facility (SECTF). The experimental results were used for proof-of-concept, for modeling radial inflow turbine rotors, and for providing data for code verification. Two rotors were designed to have a shorter axial length, up to a 10-percent reduced diameter, a lighter weight, and equal or higher efficiencies with those of conventional radial inflow turbine rotors. Three configurations were tested: rotor 1, having a 40-percent shorter axial length, with the design stator (stator 1); rotor 1 with the design stator vanes closed down (stator 2); and rotor 2, slightly shorter axially and having higher loading, with stator 2. The stator had 36 vanes and the rotors each had 14 solid blades. Although presently uncooled, the rotor blades were designed for thicknesses which would allow cooling passages to be added. The overall stage performance measurements and the rotor and stator exit flow field surveys were obtained. Measurements of steady state temperatures, pressures, mass flow rates, flow angles, and output power were made at various operating conditions. Data were obtained at corrected speeds of 80, 90, 100, 110, and 120 percent of design over a range of equivalent inlet-to-exit pressure ratios of 3.5, 4.0, 4.5, and 5.0, the maximum pressure ratio achieved. The test showed that the configuration of rotor 1 with stator 1 running at the design pressure ratio produced a flow rate which was 5.6 percent higher than expected. This result indicated the need to close down the stator flow area to reduce the flow. The flow area reduction was accomplished by restaggering the vanes. Rotor 1 was retested with the closed-down stator vanes and achieved the correct mass flow. Rotor 2 was tested only with the restaggered vanes. The test results of the three turbine configurations were nearly identical. Although the measured efficiencies of the compact designs fell 2 to 3 points below the predicted efficiency of 91 percent, they did meet and exceed by up to 2.5 percentage points the efficiences of state-of-the-art turbines found in the literature.

Simonyi, P. Susan↗
NASA NTRS2008

Optimized Non-Obstructive Particle Damping (NOPD) Treatment for Composite Honeycomb Structures

Non-Obstructive Particle Damping (NOPD) technology is a passive vibration damping approach whereby metallic or non-metallic particles in spherical or irregular shapes, of heavy or light consistency, and even liquid particles are placed inside cavities or attached to structures by an appropriate means at strategic locations, to absorb vibration energy. The objective of the work described herein is the development of a design optimization procedure and discussion of test results for such a NOPD treatment on honeycomb (HC) composite structures, based on finite element modeling (FEM) analyses, optimization and tests. Modeling and predictions were performed and tests were carried out to correlate the test data with the FEM. The optimization procedure consisted of defining a global objective function, using finite difference methods, to determine the optimal values of the design variables through quadratic linear programming. The optimization process was carried out by targeting the highest dynamic displacements of several vibration modes of the structure and finding an optimal treatment configuration that will minimize them. An optimal design was thus derived and laboratory tests were conducted to evaluate its performance under different vibration environments. Three honeycomb composite beams, with Nomex core and aluminum face sheets, empty (untreated), uniformly treated with NOPD, and optimally treated with NOPD, according to the analytically predicted optimal design configuration, were tested in the laboratory. It is shown that the beam with optimal treatment has the lowest response amplitude. Described below are results of modal vibration tests and FEM analyses from predictions of the modal characteristics of honeycomb beams under zero, 50% uniform treatment and an optimal NOPD treatment design configuration and verification with test data.

Panossian, H.↗
DOE OSTI2022

Feasibility of critical infrastructure protection using network functions for programmable and decoupled ICS policy enforcement over WAN

Industrial control systems (ICS) represent a major component of our critical infrastructure. With the increasing need for more control and monitoring of such systems, ICS have seen an increase in connectivity to wide area networks (WAN) exposing aging equipment to rapidly evolving cybersecurity threats. Furthermore, the ICS data requires a reliability measure from the networks for critical functions for infrastructure monitoring and control. Especially when remote plant sites are involved such as pipelines, energy distribution networks, and transportation, WAN transport impairments most often provide a best effort delivery with no strict reliability guarantees. Network functions can provide a vendor agnostic, programmable critical infrastructure protection with a single maintenance, policy determination, and reliability assurance surface. A network function (NF) can be utilized for policy enforcement over the communication between remote entities and the main control office. This paper presents the research on transparent integration with existing ICS without disrupting communications, resulting in minimal downtime while decoupling the fast paced evolution of defensive security measures from the upgrade cycle of expensive long term hardware. We report our measurements on the resource requirements and overhead in the network for successful NF insertion under a wide variety of network impairments (network packet delay, reordering, and loss). Our paired NF implementation provides a policy enforcement platform extensible to cover myriad cybersecurity-related communication goals, including packet signing for verification, encryption for data privacy, packet filtering and data diode operation (i.e. protecting against eavesdropping, packet injection, and denial-of-service). Furthermore, bundling communication specifications into packet flows allows for tunability in applying policies as coarse- or fine-grained as the needs of the operator. We report on network function resource requirements in the form of required queue depth and network utilization overhead to inform the decision making against hardware cost constraints.

42 ENGINEERING↗