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At least 73 records · Page 4

TPSAS-NF1676L-13664-DND

The safety of aerospace vehicles is largely dependent on the ability of modern non-destructive evaluation (NDE) tools to accurately detect structural damage before a critical flaw size is reached. However, existing NDE technologies are inherently limited by the physical response of the materials being inspected making the detection of small cracks or pre-crack damage difficult. One innovative solution to this problem is to create a multifunctional metallic material that can be used in structural applications and contains second phase sensory particles that significantly enhance the ability of conventional NDE techniques to detect incipient damage during use and at regularly scheduled inspections. Ferromagnetic shape-memory alloys (FSMAs) are an ideal material for use as this second phase material as they undergo a uniform and repeatable change in both magnetic properties and crystallographic structure when strained. These changes are more readily detected than small cracks, thereby, allowing for enhanced detection of damage by conventional NDE techniques. In this study, a multifunctional metallic material was produced by embedding the sensory material particles within an aluminum alloy to form a sensory alloy. The NDE response of the FSMA and the sensory alloy during tension/compression and fatigue loading have been investigated. These results suggest that sensory alloys can be utilized for improved on-board structural health monitoring and to improve the accuracy and reduce time for ground-based inspection.

T. A. Wallace↗

Finite Element Modeling of the Thermographic Inspection for Composite Materials

The performance of composite materials is dependent on the constituent materials selected, material structural geometry, and the fabrication process. Flaws can form in composite materials as a result of the fabrication process, handling in the manufacturing environment, and exposure in the service environment to anomalous activity. Often these flaws show no indication on the surface of the material while having the potential of substantially degrading the integrity of the composite structure. For this reason it is important to have available inspection techniques that can reliably detect sub-surface defects such as inter-ply disbonds, inter-ply cracks, porosity, and density changes caused by variations in fiber volume content. Many non-destructive evaluation techniques (NDE) are capable of detecting sub-surface flaws in composite materials. These include shearography, video image correlation, ultrasonic, acoustic emissions, and X-ray. The difficulty with most of these techniques is that they are time consuming and often difficult to apply to full scale structures. An NDE technique that appears to have the capability to quickly and easily detect flaws in composite structure is thermography. This technique uses heat to detect flaws. Heat is applied to the surface of a structure with the use of a heat lamp or heat gun. A thermographic camera is then pointed at the surface and records the surface temperature as the composite structure cools. Flaws in the material will cause the thermal-mechanical material response to change. Thus, the surface over an area where a flaw is present will cool differently than regions where flaws do not exist. This paper discusses the effort made to thermo-mechanically model the thermography process. First the material properties and physical parameters used in the model will be explained. This will be followed by a detailed discussion of the finite element model used. Finally, the result of the model will be summarized along with recommendations for future work.

Bucinell, Ronald B.↗

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗

RCC NDE Update

This slide presentation reviews non-destructive evaluation (NDE) techniques of Reinforced Carbon-Carbon (RCC) materials and the progress involved in bringing the technology to technological maturity. Included is information about the test specimens, thermographic, ultrasonic, eddy current, and radiographic inspection of RCC materials.

Hernandez, Jose M.↗

Non-destructive structural characterization of graphite components using mechanical resonance and deep learning

As compared to conventional nuclear reactors, microreactors have the potential to significantly reduce construction timelines and capital costs, decreasing the barriers for advanced nuclear reactor technologies. However, the lower power output of these microreactors (typically < 20 MWe) creates challenging economics if operation and maintenance costs cannot be sufficiently reduced. The compact size of these designs presents an opportunity for comprehensive in-situ structural health monitoring to provide real-time feedback in order to reduce operational costs associated with maintenance and downtime. Many microreactor concepts use graphite for both in-core neutron moderation and as a structural material, which has typically required some form of periodic and laborious inspection. This report provides a description and assessment of recent work with graphite to couple acoustic-based experimental measurements and characterization with machine learning models to mature structural health monitoring capabilities and generate benefits for the nuclear microreactor industry. With resilient embedded sensors in development in other programs funded by the US Department of Energy’s Office of Nuclear Energy and elsewhere, the work described herein builds upon previously funded efforts to mature non-destructive testing technology that relates measured vibrational signatures to structural changes, using a combination of new experimental measurements and machine learning processing. Building on past successful demonstrations of predictive workflows to identify structural changes in a hexagonal stainless steel test article with excellent acoustic propagation, we first performed baseline characterization on graphite samples with canonical geometries to ensure compatibility and confidence in the applied techniques for a material with distinctly different mechanical properties. In contrast to efforts in previous years, we worked exclusively with unidirectional vibration data that is more comparable to those expected from the existing embedded sensor technologies which are suitable for deployment in a reactor setting. Established acoustic and modern machine-learning-based characterization approaches were applied to the resulting datasets from these simple geometries. Both approaches were found to be highly capable of detecting even small geometric irregularities amongst nominally identical samples. As such, we then moved to testing these approaches for detection of artificial local stress perturbations introduced into a more complex geometry: a hexagonal block with drilled holes. A main outcome of this work is that a generalizable ML workflow can be used to detect and predict the characteristics of small artificial anomalies in a graphite component with a relevant geometry. While this work was performed using surficial vibration data, we expect the approach to be flexible and viable for other monitoring scenarios, such as those with different arrangements or types of sensor arrays. As compared to previously funded efforts, an existing ML workflow based on neural networks was enhanced through the addition of recently developed Fourier neural operators. As applied to previously collected and new vibration datasets, prediction accuracies of anomaly characterizations were greatly improved with minimal added computational cost. As trained on small durations of vibration data (tens of seconds) collected over a realistic number of locations, the model was able to reliably determine the presence of a subtle stress anomaly and begin to provide location estimates. Such an approach is likely to be viable for more relevant reactor damage scenarios for graphite components, such as progressive crack growth or creep.

36 MATERIALS SCIENCE↗

Characteristics of Ferromagnetic Flux Focusing Lens in the Development of Surface/Subsurface Flaw Detector

Electromagnetic NDE techniques have in the past steered away from the use of ferromagnetic materials. Although their high permeabilities lead to increased field levels, the properties of ferrous elements in the presence of alternating magnetic fields are difficult to determine. In addition, their use leads to losses which can be minimized through the use of low conductivity ferrites. In fact, the eddy current probes which do incorporate ferromagnetic materials have focused on these losses and the shielding which can be obtained by surrounding a probe with a high permeability, conducting material. Eddy current probes enclosed in conducting and magnetic shields have been used to prevent the generated fields from interacting with materials in the vicinity of the probe, such as when testing near material boundaries. A recent invention has used ferromagnetic shielding to magnetically separate individual concentric eddy current probes in order to eliminate cross-talk between the probes so that simultaneous detection of different types of flaws at different depths can be achieved. In contrast to the previous uses of ferromagnetic materials purely as magnetic shields, an electromagnetic flaw detector recently developed at NASA Langley Research Center takes advantage of the flux focusing properties of a ferromagnetic mild steel in order to produce a simple, effective device for the non-destructive evaluation of conducting materials. The Flux Focusing Eddy Current Probe has been shown to accurately measure material thickness and fatigue damage. The straight forward flaw response of the probe makes the device ideal for rapid inspection of large structures, and has lead to its incorporation in a computer controlled search routine to locate fatigue crack tips and monitor experimental fatigue crack growth experiments.

Wincheski, Buzz↗

Industrial Inspection System

ACTIS+ is a smaller, personal computer version of ACTIS, a computed tomography system which finds its origins in the Apollo lunar landing research. It is used to identify imperfections in aerospace structures and components. Designed to be added to an existing real time radiography system, its components include a high precision rotation/elevation manipulator, color image monitor, graphical user interface monitor, and PC compatible workstation. Cross-sectional CT images are more detailed than radiographic images and the high speed scanning feature offers the capability for 100 percent inspection in a production environment. Bio-Imaging Research, Inc. (BIR) originally developed ACTIS for Marshall Space Flight Center (MSFC), and commercial units were sold to aerospace manufacturers. The technology was refined for ACTIS+, which is principally used in non-destructive testing.

Source record↗

Statistical Analysis of an Infrared Thermography Inspection of Reinforced Carbon-Carbon

Each piece of flight hardware being used on the shuttle must be analyzed and pass NASA requirements before the shuttle is ready for launch. One tool used to detect cracks that lie within flight hardware is Infrared Flash Thermography. This is a non-destructive testing technique which uses an intense flash of light to heat up the surface of a material after which an Infrared camera is used to record the cooling of the material. Since cracks within the material obstruct the natural heat flow through the material, they are visible when viewing the data from the Infrared camera. We used Ecotherm, a software program, to collect data pertaining to the delaminations and analyzed the data using Ecotherm and University of Dayton Log Logistic Probability of Detection (POD) Software. The goal was to reproduce the statistical analysis produced by the University of Dayton software, by using scatter plots, log transforms, and residuals to test the assumption of normality for the residuals.

Comeaux, Kayla↗

Design of a Borescope for Extravehicular Non-Destructive Applications

Anomalies such as corrosion, structural damage, misalignment, cracking, stress fiactures, pitting, or wear can be detected and monitored by the aid of a borescope. A borescope requires a source of light for proper operation. Today s current lighting technology market consists of incandescent lamps, fluorescent lamps and other types of electric arc and electric discharge vapor lamp. Recent advances in LED technology have made LEDs viable for a number of applications, including vehicle stoplights, traffic lights, machine-vision-inspection, illumination, and street signs. LEDs promise significant reduction in power consumption compared to other sources of light. This project focused on comparing images taken by the Olympus IPLEX, using two different light sources. One of the sources is the 50-W internal metal halide lamp and the other is a 1 W LED placed at the tip of the insertion tube. Images acquired using these two light sources were quantitatively compared using their histogram, intensity profile along a line segment, and edge detection. Also, images were qualitatively compared using image registration and transformation [l]. The gray-level histogram, edge detection, image profile and image registration do not offer conclusive results. The LED light source, however, produces good images for visual inspection by an operator. Analysis using pattern recognition using Eigenfaces and Gaussian Pyramid in face recognition may be more useful.

Bachnak, Rafic↗

Current and future developments in civil aircraft non-destructive evaluation from an operator's point of view

In June, 1988, the first International Conference on aging aircraft was held to address nondestructive tests (NDT) of aging aircraft and other issues. From this meeting, a research program was initiated and funded by the FAA. As a result of this program, a lot of work has been done to study current NDT practices in the aviation industry and secondly, to research and develop new NDT methods to improve the reliability and efficiency of in-service inspection of aircraft structures and powerplants. The following is an overview of the current and future developments in civil aircraft NDT, as viewed by an air carrier and the concerns for NDT in the future.

Aging Aircraft↗

Modal Test Technology as Non-Destructive Evaluation of Space Shuttle Structures

Modal test and analysis Is being used for nondestructive evaluation of Space Shuttle structures. The purpose of modal testing is to measure the dynamic characteristics of a structure to extract its resonance frequencies, damping, and mode shapes. These characteristics are later compared to subsequently acquired characteristics. Changes in the modal characteristics indicate damage in the structure. Use of modal test technology as a damage detection tool was developed at JSC during the Shuttle acoustic certification program and subsequent test programs. The Shuttle Modal Inspection System was created in order to inspect areas that are impossible or impractical to inspect with conventional methods. Areas on which this technique has been applied include control surfaces, which are covered with thermal protection tiles, and the Forward Reaction Control Module, which is a frame structure that supports various tanks, thrusters, and fluid lines, which requires major disassembly to inspect. This paper traces the development of the technology, gives a status of its implementation on the Shuttle, explains challenges involved in implementing this type of inspection program, and suggests future improvements in data analysis and interpretation. Dual-use applications of the technology include inspections of bridges, oil-platforms, and aircraft.

Micheal S Grygler↗

Developing NDE Techniques for Large Cryogenic Tanks - Year 2 Report

The Shuttle Program requires very large cryogenic ground storage tanks in which to store liquid oxygen and hydrogen. The existing Launch Complex-39 Pad tanks, which will be passed onto future launch programs, are over 40 years old and have received minimal refurbishment and only external inspections over the years. The majority of the structure is inaccessible without a full system drain of cryogenic liquid and insulation in the annular region. It was previously thought that there was a limit to the number of temperature cycles that the tanks could handle due to possible insulation compaction before undergoing a costly and time consuming complete overhaul; therefore the tanks were not drained and performance issues with these tanks, specifically the Pad B LH2 tank, were accepted. There is a need and an opportunity, as the Shuttle program ends and work to upgrade the launch pad progresses, to develop innovative non-destructive evaluation (NDE) techniques to analyze the current tanks. Techniques are desired that can aid in determining the extent of refurbishment required to keep the tanks in service for another 20+ years. A non-destructive technique would also be a significant aid in acceptance testing of new and refurbished tanks, saving significant time and money, if corrective actions can be taken before cryogen is introduced to the systems. Year one of this project concentrated on analysis of the current tanks located at LC-39 while cryogen was present. Year two of this project concentrated on analysis of detectable thermal variations on the outer surface of the tanks as the cryogen was drained and the inner vessel warmed to ambient conditions. Two techniques have been deployed in the field to monitor the tank. The first consisted of a displacement sensor to monitor for any expansions at the base of the tank during warm-up that could indicate a compaction issue with the insulation. The second technique was continued thermal monitoring of the tank through and after warm up. The indications noted in the thermal images were compared to bore-scope images of the annular region taken once the tank was inert and warmed to ambient conditions. Similar thermal imaging was performed on a smaller tank where an insulation void was induced to compare the effectiveness of thermal imagining on a different tank geometry.

Arens, Ellen↗

Developing NDE Techniques for Large Cryogenic Tanks

The Shuttle Program requires very large cryogenic ground storage tanks in which to store liquid oxygen and hydrogen. The existing Pads A and B Launch Complex-39 tanks, which will be passed onto future launch programs, are 45 years old and have received minimal refurbishment and only external inspections over the years. The majority of the structure is inaccessible without a full system drain of cryogenic liquid and granular insulation in the annular region. It was previously thought that there was a limit to the number of temperature cycles that the tanks could handle due to possible insulation compaction before undergoing a costly and time consuming complete overhaul; therefore the tanks were not drained and performance issues with these tanks, specifically the Pad B liquid hydrogen tank, were accepted. There is a needind an opportunity, as the Shuttle program ends and work to upgrade the launch pads progresses, to develop innovative non-destructive evaluation (NDE) techniques to analyze the current tanks. Techniques are desired that can aid in determining the extent of refurbishment required to keep the tanks in service for another 20+ years. A nondestructive technique would also be a significant aid in acceptance testing of new and refurbished tanks, saving significant time and money, if corrective actions can be taken before cryogen is introduced to the systems.

Parker, Don↗

Monte Carlo N-Particle Transport Performance of Predicting Digital Radiographic IQI Inspection

The identification of porosity, geometric noncompliance, and other defect types are critical to the qualification of materials and components. X-ray radiographic nondestructive testing is a common industrial inspection method for process quality control and component qualification and certification. Digital radiography provides a quick and efficient alternative when compared to traditional film-based inspection. The quality of radiographic inspection is dependent on equipment specifications, such as the source spot size and detector pixel size, and the specific parameters selected for use for the radiographic technique. To evaluate if an x-ray system and technique is sufficient for a given requirement, a radiographic image quality indicator (IQI) can be used. Radiographic IQIs in hard to machine materials or hard to manufacture defects can be time consuming and expensive to manufacture. This study was conducted to evaluate current Savannah River National Laboratory (SRNL) x-ray imaging systems with a custom tantalum IQI and using Monte Carlo simulations to predict the performance of future systems. The tantalum IQI was tested using a Siefert Isovolt 420 keV x-ray tube with a Perkin Elmer XRD 1611 flat panel with 100-micron pixels. Using the Monte Carlo N-Particle transport software, the radiographic tally was used to simulate the photon flux through an identical tantalum IQI. These simulations provided a benchmark as to the best theoretical identification on a given system using our tantalum IQI. The simulations were refined to match SRNL’s current systems’ noise levels, leading to confidence in their ability to predict the performance of other systems that may be purchased and deployed in the future at the Savannah River Site. Future studies will be conducted to prove this research can be extended to artificially evaluate the ability for systems to identify critical defect sizes through x-ray radiographic inspection, drastically reducing the cost and time burdens of producing high-fidelity radiographic test articles.

digital X-ray radiography↗

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗

Composite Overwrapped Pressure Vessels (COPV): Developing Flight Rationale for the Space Shuttle Program

Introducing composite vessels into the Space Shuttle Program represented a significant technical achievement. Each Orbiter vehicle contains 24 (nominally) Kevlar tanks for storage of pressurized helium (for propulsion) and nitrogen (for life support). The use of composite cylinders saved 752 pounds per Orbiter vehicle compared with all-metal tanks. The weight savings is significant considering each Shuttle flight can deliver 54,000 pounds of payload to the International Space Station. In the wake of the Columbia accident and the ensuing Return to Flight activities, the Space Shuttle Program, in 2005, re-examined COPV hardware certification. Incorporating COPV data that had been generated over the last 30 years and recognizing differences between initial Shuttle Program requirements and current operation, a new failure mode was identified, as composite stress rupture was deemed credible. The Orbiter Project undertook a comprehensive investigation to quantify and mitigate this risk. First, the engineering team considered and later deemed as unfeasible the option to replace existing all flight tanks. Second, operational improvements to flight procedures were instituted to reduce the flight risk and the danger to personnel. Third, an Orbiter reliability model was developed to quantify flight risk. Laser profilometry inspection of several flight COPVs identified deep (up to 20 mil) depressions on the tank interior. A comprehensive analysis was performed and it confirmed that these observed depressions were far less than the criterion which was established as necessary to lead to liner buckling. Existing fleet vessels were exonerated from this failure mechanism. Because full validation of the Orbiter Reliability Model was not possible given limited hardware resources, an Accelerated Stress Rupture Test of a flown flight vessel was performed to provide increased confidence. A Bayesian statistical approach was developed to evaluate possible test results with respect to the model credibility and thus flight rationale for continued operation of the Space Shuttle with existing flight hardware. A non-destructive evaluation (NDE) technique utilizing Raman Spectroscopy was developed to directly measure the overwrap residual stress state. Preliminary results provide optimistic results that patterns of fluctuation in fiber elastic strains over the outside vessel surface could be directly correlated with increased fiber stress ratios and thus reduced reliability.

Kezirian, Michael T.↗

Infrared thermography NDT for in-situ defect detection in sandwich composite panel manufacturing

Composite manufacturing presents numerous challenges, as defects can arise from various sources throughout the process. In sandwich composite structures, the integration of a foam core introduces additional complexity and increases the likelihood of defect formation like delamination. To mitigate these issues and reduce the risk of future structural failures, in-situ monitoring during manufacturing is essential. This study investigates infrared (IR) thermography as a non-destructive technique for detecting manufacturing defects in foam-core sandwich composite panels under thermally excited conditions representative of in-situ processing. A stationary FLIR A8590 IR camera (640 × 512 pixels, 30Hz, 17mm lens, 9 ft stand-off distance) was used to monitor prefabricated panels subjected to controlled external heating simulating compression molding and resin cure exotherm. Interlaminar delamination defects with characteristic sizes ranging from 0.25 × 0.25in² to 5 × 5in² produced measurable surface temperature depressions of approximately 4–10°C during transient cooling, exceeding the effective noise floor of the camera by more than two standard deviations. Thicker laminates exhibited prolonged defect detectability windows due to increased thermal diffusion time. In contrast, embedded Teflon inclusions generated weak thermal contrasts of ≤ 3°C, approaching the measurement noise floor, due to limited thermal property contrast with the surrounding glass fiber composite. These results establish quantitative detectability limits for stationary thermographic inspection of sandwich composite panels under manufacturing-representative thermal cycles.

Barakat, Abdallah [ORNL] (ORCID:0000000296141398)↗

Utilization of Unmanned Aircraft Systems for Environmental Purposes at the Savannah River Site – 26578

Born in the 1950s, the Savannah River Plant was constructed as a plutonium and tritium production plant. As the Cold War era came and went, a change of direction was signaled when the name of the facility changed from Savannah River Plant to Savannah River Site (1989) – the main mission at Savannah River shifted from “production” to “cleanup.” The Department of Energy is responsible for managing the 310 square miles of land that is the Savannah River Site and the cleanup/remediation activities that occur. The Savannah River National Laboratory utilizes unmanned aircraft systems to assist with some of those environmental monitoring and remediation activities. One function of unmanned aircraft systems at the Savannah River National Laboratory is conducting aerial photography and videography. Various infrastructure evaluations have been performed with unmanned aircraft – facility rooftop inspections, water tower lock verifications, earthen dam surveys, etc. An unmanned aircraft system has been used for progress footage of remediation projects – Dunbarton Bay remediation, Saltstone Disposal Unit construction, etc. Thermal cameras on an unmanned aircraft system are used to help identify cracks/leaks in structures from vantage points not readily accessible by personnel. Virtual tours of different waste units are conducted with unmanned aircraft systems for Site groups and federal/state regulators to save costs and travel time. Additionally, advanced remote sensing technologies are used on unmanned aircraft systems at the Savannah River Site. Light Detection and Ranging uses laser pulses to measure distances to the Earth's surface or other targets to create highly detailed topographic maps that accurately portray terrain (e.g., elevation changes, slopes, and contours). Data collection with a Light Detection and Ranging unit mounted on an unmanned aircraft system is quick and efficient – large-area surveys are conducted in shorter time frames. Because Light Detection and Ranging can penetrate through foliage and vegetation to ground level, it is being used in conjunction with a watershed model to study the General Separations Area of the Site to determine stormwater flow volume and direction, monitor stream stability, and forecast river flow behavior. A hyperspectral camera captures a wide spectrum of electromagnetic wavelengths across numerous narrow bands, beyond what the human eye can see. It provides detailed spectral information about the objects or surfaces in an image, which can be used to identify and analyze materials based on their spectral signatures. A hyperspectral camera mounted on an unmanned aircraft system has been used at the Savannah River Site for non-destructive evaluation of concrete and concrete structures. Unmanned aircraft systems at the Savannah River Site are also used for the application of herbicide on identified rooftops. P-Reactor and R-Reactor are entombed nuclear reactors at the Savannah River Site. Unwanted vegetation is often present on these rooftops – over time roots can penetrate seams, cracks, and joints of the general roof and concrete caps, leading to water ingress and deterioration of the structural components. For time and cost efficiencies as well as in the interest of personnel safety, an unmanned aircraft is used to dispense herbicide on rooftop areas where vegetation is noticed to help alleviate the issues/hazards.

Lorier, Troy [Savannah River National Laboratory (↗