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All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Quantitative analysis of geomorphic processes using satellite image data at different scales

When aerial and satellite photographs and images are used in the quantitative analysis of geomorphic processes, either through direct observation of active processes or by analysis of landforms resulting from inferred active or dormant processes, a number of limitations in the use of such data must be considered. Active geomorphic processes work at different scales and rates. Therefore, the capability of imaging an active or dormant process depends primarily on the scale of the process and the spatial-resolution characteristic of the imaging system. Scale is an important factor in recording continuous and discontinuous active geomorphic processes, because what is not recorded will not be considered or even suspected in the analysis of orbital images. If the geomorphic process of landform change caused by the process is less than 200 m in x to y dimension, then it will not be recorded. Although the scale factor is critical, in the recording of discontinuous active geomorphic processes, the repeat interval of orbital-image acquisition of a planetary surface also is a consideration in order to capture a recurring short-lived geomorphic process or to record changes caused by either a continuous or a discontinuous geomorphic process.

Williams, R. S., Jr.↗
NASA NTRS1996

Cost Models for MMC Manufacturing Processes

The quality cost modeling (QCM) tool is intended to be a relatively simple-to-use device for obtaining a first-order assessment of the quality-cost relationship for a given process-material combination. The QCM curve is a plot of cost versus quality (an index indicating microstructural quality), which is unique for a given process-material combination. The QCM curve indicates the tradeoff between cost and performance, thus enabling one to evaluate affordability. Additionally, the effect of changes in process design, raw materials, and process conditions on the cost-quality relationship can be evaluated. Such results might indicate the most efficient means to obtain improved quality at reduced cost by process design refinements, the implementation of sensors and models for closed loop process control, or improvement in the properties of raw materials being fed into the process. QCM also allows alternative processes for producing the same or similar material to be compared in terms of their potential for producing competitively priced, high quality material. Aside from demonstrating the usefulness of the QCM concept, this is one of the main foci of the present research program, namely to compare processes for making continuous fiber reinforced, metal matrix composites (MMC's). Two processes, low pressure plasma spray deposition and tape casting are considered for QCM development. This document consists of a detailed look at the design of the QCM approach, followed by discussion of the application of QCM to each of the selected MMC manufacturing processes along with results, comparison of processes, and finally, a summary of findings and recommendations.

Elzey, Dana M.↗
NASA NTRS1994

The r-, s-, and p-Processes in Nucleosynthesis

Burbidge et al (1957) and Cameron (1957) laid out the framework for our understanding of the formation of the heavy nuclei (those nuclei with mass number A approx. greater than 70). From systematics in the solar system abundance distribution, Burbidge et al determined that the heavy nuclei were formed in three distinct nucleosynthetic processes, which they termed the r-, s-, and p-processes. That we still use these terms today is a credit to the soundness of this work done 37 years ago. We may understand how Burbidge et al and Cameron arrived at their conclusions from Figure 1. One population of nuclei, the s-nuclei, shows an abundance distribution with peaks near mass numbers 87, 138, and 208. These nuclei are made in a slow neutron-capture process, the s-process. A rapid neutron-capture process, the r-process, is responsible for the r-nuclei, whose abundance distribution shows peaks at mass numbers 80, 130, and 195. The p-process is responsible for production of the rarer, more proton-rich heavy isotopes (the p-nuclei) that cannot be made by neutron capture. The first quantitative evaluations of the ideas of Burbidge et al and Cameron came to light in the early 1960s with work on the s-process (Clayton et al 1961, Seeger et al 1965) and the r-process (Seeger et al 1965). These calculations further elucidated the mechanisms for heavy-element formation and showed the plausibility of the framework developed in the 1950s. Subsequent work has focused on determining the astrophysical sites where the r-, s-, and p-processes occurred with the help of improved nuclear details, stellar models, and abundances. A goal of this paper is to review the recent progress astrophysicists, astronomers, and physicists have made in these directions and to point out the problems that remain in our understanding of the formation of the heavy nuclei. Another, perhaps deeper, goal is to to seek some understanding of why there are three major processes available to nature for synthesis of heavy elements. It is impossible for a single paper to cover all relevant aspects of the r-, s-, and p-processes; therefore, where possible, references to other reviews are given. Readers should turn to these reviews for more details. Nevertheless, it is hoped that the present paper gives some flavor for the rich field of heavy-element synthesis.

Meyer, Bradley S.↗
DOE OSTI2013

Extensible packet processing architecture

A technique for distributed packet processing includes sequentially passing packets associated with packet flows between a plurality of processing engines along a flow through data bus linking the plurality of processing engines in series. At least one packet within a given packet flow is marked by a given processing engine to signify by the given processing engine to the other processing engines that the given processing engine has claimed the given packet flow for processing. A processing function is applied to each of the packet flows within the processing engines and the processed packets are output on a time-shared, arbitered data bus coupled to the plurality of processing engines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Collaborative Research: Process-resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The future projection of the ENSO and AM variability, however, remains highly uncertain with the state-of-the-art coupled general circulation models. A comprehensive understanding of the factors responsible for the inter-model discrepancies in projecting future changes in the ENSO and AM variability, in terms of multiple feedback processes involved, has yet to be achieved. The proposed research aims to identify sources of such uncertainty and establish a set of process-resolving quantitative evaluations of the existing predictions of the future ENSO and AM variability. The proposed process-resolving evaluations are based on a feedback analysis method formulated in Lu and Cai (2009), which is capable of partitioning 3D temperature anomalies/perturbations into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. Taking advantage of the high-resolution, multi-model ensemble products from the Coupled Model Intercomparison Project Phase 5 (CMIP5) soon to be available at the Lawrence Livermore National Lab, we will conduct a process-resolving decomposition of the global three-dimensional (3D) temperature (including SST) response to the ENSO and AM variability in the preindustrial, historical and future climate simulated by these models. Specific research tasks include 1) identifying the model-observation discrepancies in the global temperature response to ENSO and AM variability and attributing such discrepancies to specific feedback processes, 2) delineating the influence of anthropogenic radiative forcing on the key feedback processes operating on ENSO and AM variability and quantifying their relative contributions to the changes in the temperature anomalies associated with different phases of ENSO and AMs, and 3) investigating the linkages between model feedback processes that lead to inter-model differences in time-mean temperature projection and model feedback processes that cause inter-model differences in the simulated ENSO and AM temperature response. Through a thorough model-observation and inter-model comparison of the multiple energetic processes associated with ENSO and AM variability, the proposed research serves to identify key uncertainties in model representation of ENSO and AM variability, and investigate how the model uncertainty in predicting time-mean response is related to the uncertainty in predicting response of the low-frequency modes. The proposal is thus a direct response to the first topical area of the solicitation: Interaction of Climate Change and Low Frequency Modes of Natural Climate Variability. It ultimately supports the accomplishment of the BER climate science activity Long Term Measure (LTM): "Deliver improved scientific data and models about the potential response of the Earth's climate and terrestrial biosphere to increased greenhouse gas levels for policy makers to determine safe levels of greenhouse gases in the atmosphere."

58 GEOSCIENCES↗
DOE OSTI2011

CHARACTERIZING THE HEAVY ELEMENTS IN GLOBULAR CLUSTER M22 AND AN EMPIRICAL s-PROCESS ABUNDANCE DISTRIBUTION DERIVED FROM THE TWO STELLAR GROUPS

We present an empirical s-process abundance distribution derived with explicit knowledge of the r-process component in the low-metallicity globular cluster M22. We have obtained high-resolution, high signal-to-noise spectra for six red giants in M22 using the Magellan Inamori Kyocera Echelle spectrograph on the Magellan-Clay Telescope at Las Campanas Observatory. In each star we derive abundances for 44 species of 40 elements, including 24 elements heavier than zinc (Z = 30) produced by neutron-capture reactions. Previous studies determined that three of these stars (the 'r+s group') have an enhancement of s-process material relative to the other three stars (the 'r-only group'). We confirm that the r+s group is moderately enriched in Pb relative to the r-only group. Both groups of stars were born with the same amount of r-process material, but s-process material was also present in the gas from which the r+s group formed. The s-process abundances are inconsistent with predictions for asymptotic giant branch (AGB) stars with M {<=} 3 M{sub Sun} and suggest an origin in more massive AGB stars capable of activating the {sup 22}Ne({alpha},n){sup 25}Mg reaction. We calculate the s-process 'residual' by subtracting the r-process pattern in the r-only group from the abundances in the r+s group. In contrast to previous r- and s-process decompositions, this approach makes no assumptions about the r- and s-process distributions in the solar system and provides a unique opportunity to explore s-process yields in a metal-poor environment.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Loquacious-PD removes phosphate inhibition of Dicer-2 processing of hairpin RNAs into siRNAs

Highlights: • Inorganic phosphate inhibits Dicer-2 processing of hairpin RNAs. • Phosphate does not inhibit Dicer-2 + Loqs-PD processing of blunt-end hairpin RNAs. • Loqs-PD removes phosphate inhibition of Dicer-2 processing of blunt hairpin RNAs. Drosophila Dicer-2 processes RNA substrates into short interfering RNAs (siRNAs). Loquacious-PD (Loqs-PD), a dsRNA-binding protein that associates with Dicer-2, is required for processing of a subset of RNA substrates including hairpin RNAs into siRNAs. Inorganic phosphate—a small molecule present in all cell types—inhibits Dicer-2 from processing precursor of microRNAs (pre-miRNAs), which are processed by Dicer-1. Whether or how Loqs-PD modulates the inhibitory effect of inorganic phosphate on Dicer-2 processing of RNA substrates is unknown. To address this question, I performed in vitro hairpin RNA processing assay with Dicer-2 in the presence or absence of Loqs-PD and/or inorganic phosphate. I found that inorganic phosphate inhibits Dicer-2 alone, but not Dicer-2 + Loqs-PD, from processing blunt-end hairpin RNAs into siRNAs. Thus, Loqs-PD removes the inhibitory effect of inorganic phosphate on Dicer-2 processing of blunt-end hairpin RNAs, allowing siRNA production in the presence of inorganic phosphate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Process-informed adsorbent design guidelines for direct air capture

Direct air capture using solid adsorbents is a proven technology critical to reducing our net greenhouse gas emissions to zero and beyond. Currently, academic research into the technology mainly focuses on the development of new adsorbents. However, there is a discord between the adsorbent design and process performance. Many materials scientists focus on maximising metrics such as the CO 2 capacity of their adsorbent. Here, we combine detailed process modelling, machine learning, and extensive global sensitivity analysis, which entails varying all of the model parameters together, on a direct air capture process to show that the dry CO 2 adsorption capacity does not influence process performance for an amine-functionalised adsorbent operating in a temperature vacuum swing adsorption (TVSA) process, while it is important in a steam-assisted TVSA (S-TVSA) process. In fact, adsorption kinetics, density, and thermal conductivity are all critical attributes to obtaining a low energy penalty and reduced costs. The analysis also highlights the importance of heat transfer, directing process engineers to (alternative) adsorber designs that maximise this. By an in-depth evaluation of how process performance indicators are affected by materials properties and process operating parameters, this work provides guidance to both material scientists and process engineers towards the design of a “unicorn adsorbent” and intensified DAC processes. This will improve the performance of solid adsorbent direct air capture and help drive down the costs of this vital technology to avert the worst impacts of climate change.

42 ENGINEERING↗
NASA NTRSDate not supplied

Metal Additive Manufacturing Process Selection and Development for Propulsion Components

Metal additive manufacturing (AM) is a generic term that captures a variety of fabrication processes. Each of these manufacturing process has unique advantages and challenges for use in aerospace propulsion applications. The most commonly used AM processes include Powder Bed Fusion (PBF), Directed Energy Deposition (DED), and solid-state processes as in Cold Spray, Ultrasonic Additive Manufacturing, and Additive Friction Stir Deposition. While detailed research has been conducted among many of the AM processes to mature processing parameters and material properties, navigating which processes are best to select is difficult as it is based on specific component requirements. The focus of this presentation is to provide an overview of considerations for each of metal AM process selection for aerospace components based on various key attributes. These key attributes include geometric considerations, metallurgical characteristics, cost basis, post-processing and maturity of the processes. The data for these trade selections are based on studies that NASA as performed internally and with academic and industry partners. These studies include multiple AM build experiments to evaluate (1) geometric variations and constraints within the processes, (2) alloy characterization and mechanical testing, (3) pathfinder component development and hot-fire evaluations, and (4) certification approaches. This presentation summarizes these results and is meant to introduce specific examples which show what to consider when designing a metal AM component for aerospace propulsion applications.

Additive Manufacturing↗
NASA NTRSDate not supplied

Powder Bed Fusion Laser Beam Metals Additive Manufacturing: Process Monitoring Approaches for Qualification and Certification

The use of in-situ process monitoring is of interest to lower the cost of inspection for the qualification of powder bed fusion laser beam metal (PBF-LB/M) additively manufactured (AM) parts. Precise monitoring of the PBF-LB/M AM build process constitutes a multi-scale and multi-discipline task. There are several significant challenges to the in-situ approach: the synchronization of sensor signals to process steps; the physical interpretation and classification of sensor signals; managing very large datasets; and comparing the inputs with the observed monitoring signals. At NASA Langley Research Center, a configurable architecture additive testbed has been developed to monitor the build process with synchronized sensors. The philosophy and method adopted for the synchronization of the cameras with laser power and position throughout a complex PBF-LB/M AM build will be described. The synchronized in-situ monitoring signals are compared with ex-situ nondestructive inspection, x-ray computed tomography (XCT). Such comparisons permit a better understanding of how the sequential process actions of LPBF-AM can affect build quality. The multi-scale and complex process of printing additively manufactured (AM) parts can have unexpected, but predictable, build conditions that result in material microstructure variability. This presentation will describe an additive manufacturing model-based process metric (AM-PM) computational method that is a fully parallel reduced order modeling approach developed to evaluate the evolution of AM processes. This method couples the known sequence of the AM process with a physically informed nearest neighbors’ calculation to map the conditions of a part-scale build. The result is a map of the build that is derived directly from build files or in-situ process monitoring sensors. The methodology of the approach will be described and mapped to the porosity observed from XCT for a complex PBF-LB/M build. Such comparative results develop understanding of how the sequential process actions can affect the PBF-LB/M AM build quality and microstructure variability.

Laser Powder Bed Fusion↗
DOE OSTI2013

Minor actinide separation: simplification of the DIAMEX-SANEX strategy by means of novel SANEX processes

The separation of An(III) from PUREX raffinate has previously been demonstrated by applying a DIAMEX process (i.e., co-extraction of An(III) and Ln(III) from HAR) followed by a SANEX process (i.e., selective extraction of An(III) from the DIAMEX product containing An(III) + Ln(III)). In line with process intensification issues, more compact processes have been developed: Recently, a 1c-SANEX process test was successfully performed, directly extracting An(III) from PUREX HAR. More recently, a new i-SANEX process was successfully tested. This process is based on the co-extraction of An(III) + Ln(III) into a TODGA solvent, followed by a selective back-extraction of An(III) by a water soluble complexing agent, in this case SO{sub 3}-Ph-BTP. In both cases, good recoveries were achieved, and very pure product solutions were obtained. However, both 1c-SANEX and i-SANEX used non-CHON chemicals. Nevertheless, these processes are a simplification to the DIAMEX + SANEX process as only one solvent is used. Finally, the new i-SANEX process is the most compact process. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Optimal Control of Biomass Feedstock Processing System Under Uncertainty in Biomass Quality

Planning of biorefinery operations is complicated by the stochastic nature of physical and chemical characteristics of biomass feedstock, such as, moisture level and carbohydrate content. Biomass characteristics affect the performance of the equipment which feed the reactor and the efficiency of the conversion process in a biorefinery. We propose a stochastic optimization model to identify a blend of feedstocks, inventory levels, and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor while meeting the requirements of the biochemical conversion process. We propose a sample average approximation (SAA) of the model, and develop an efficient algorithm to solve the SAA model. A feedstock preprocessing process consists of two-stage grinding and pelleting is used to develop a case study. Extensive numerical analysis are conducted which lead to a number of observations. Our main observation is that sequencing bales based on moisture level and carbohydrate content leads to robust solutions that improve processing time and processing rate of the reactor. We provide a number of managerial insights that facilitate the implementation of the model proposed. Note to Practitioners—This paper is motivated by the challenges faced in the bioenergy industry. The focus of this paper is on plants which use the biochemical conversion process to generate liquid fuels. It has been observed that variations in biomass characteristics, such as moisture content, cause variations in feeding of the system which lead to under-utilization of equipment. A requirement of biochemical conversion process is to maintain the carbohydrate content of biomass processed by the reactor, larger than a threshold. We propose a model that identifies the inventory levels and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor. The goal is to improve equipment utilization while satisfying the requirements of the conversion process. The model is tested using real-life data. We found out that by sequencing bales based on moisture level and carbohydrate content, a plant can reduce variability in the system leading to improved system reliability, higher processing rates of the reactor, and higher throughput.

09 BIOMASS FUELS↗
DOE OSTI2021

Kraft black liquor concentration with graphene oxide membranes: Process simulations and technoeconomic analysis

Abstract Black liquor (BL) dewatering by multi‐effect evaporation in the kraft papermaking process is highly energy‐intensive. It was previously shown that graphene oxide (GO) nanofiltration membranes can remove lignin, other organics, and inorganic salts from BL while exhibiting stability in caustic BL conditions. Here, we design and simulate several candidate dewatering processes and evaluate their technoeconomic characteristics. All processes concentrate BL from 15 to 30 wt% solutes while producing aqueous permeate. Two process options were analyzed—option A including “last‐mile” permeate treatment to reduce solutes to 0.2 wt%, and option B excluding this treatment and producing a 3–4 wt% solutes stream. These processes were simulated in custom‐built ASPEN Plus flowsheets interfaced with Microsoft Excel and MATLAB. All processes deliver large (>40%) energy savings. Detailed technoeconomic analysis showed that option A processes are profitable in mills equipped with condensing turbines, but unprofitable with only purchased fuel savings. Option B processes are profitable in both situations, but require the caustic permeate to be utilized in other kraft process units. They are also profitable with electricity generation when operated at smaller scales matching the requirements of other process units. Monte‐Carlo sensitivity analysis shows that Option A can yield median 20‐year NPVs up to ~$10MM and Option B up to ~$25MM. Overall, GO membrane‐based BL dewatering is economically promising, assuming successful slipstream piloting and scale‐up campaigns. It would have immediate sustainability benefits from large energy savings, and broader implications for biorefinery processes due to the ability to fractionate biomass feedstock components under harsh conditions.

Wang, Zhongzhen↗
DOE OSTI2024

Intensified biogas to liquid (IBGTL) Process: Experimental validation and modeling analysis

The Intensified Biogas to Liquid (IBGTL) process aims to overcome traditional economy-of-scale barriers in biogas-to-liquid fuel production by integrating bi-reforming and Fischer-Tropsch synthesis (FTS) in a single IBGTL reactor. This reactor operates at uniform pressure with different optimized temperatures across two zones for efficient conversion, utilizing multifunctional bi-reforming catalysts and high-temperature FTS catalysts. Bench scale experiments were carried out using landfill gas (LFG) in a single pass process, and the yield data from these experiments were fed into process scale-up design and techno-economic analysis (TEA) across four scenarios: (1) a single pass process, (2) a process with material recycling, (3) a process with liquefied petroleum gas (LPG) co-product recovery, and (4) a process with electricity generation from the fuel gas produced. TEA identified Scenario 2 as the most cost-effective, achieving a Minimum Fuel Selling Price (MFSP) of $\$4.59$ per gallon, competitive with the current national diesel price of $\$4.7$ per gallon. However, comparison with the conventional two-reactor system highlights the need for catalyst performance improvements. Sensitivity analysis emphasized the importance of manufacturing cost, liquid fuel yield, and biogas flow rate. Further analysis determined that the IBGTL process must achieve a diesel mass yield beyond 11.7% to surpass the economic viability of the conventional TriFTS (Tri-reforming followed by Fischer-Tropsch Synthesis) process. If the IBGTL process attains the TriFTS yield of up to 17%, the resulting MFSP could be approximately 31% lower than the current TriFTS MFSP. Furthermore, renewable energy credits and carbon credits can further enhance the economic viability of BGTL processes.

09 BIOMASS FUELS↗
DOE OSTI2020

Predicting lake surface water phosphorus dynamics using process-guided machine learning

Phosphorus (P) loading to lakes is degrading the quality and usability of water globally. Accurate predictions of lake P dynamics are needed to understand whole-ecosystem P budgets, as well as the consequences of changing lake P concentrations for water quality. However, complex biophysical processes within lakes, along with limited observational data, challenge our capacity to reproduce short-term lake dynamics needed for water quality predictions, as well as long-term dynamics needed to understand broad scale controls over lake P. Here we use an emerging paradigm in modeling, process-guided machine learning (PGML), to produce a phosphorus budget for Lake Mendota (Wisconsin, USA) and to accurately predict epilimnetic phosphorus over a time range of days to decades. In our implementation of PGML, which we term a Process-Guided Recurrent Neural Network (PGRNN), we combine a process-based model for lake P with a recurrent neural network, and then constrain the predictions with ecological principles. We test independently the process-based model, the recurrent neural network, and the PGRNN to evaluate the overall approach. The process-based model accounted for most of the observed pattern in lake P; however it missed the long-term trend in lake P and had the worst performance in predicting winter and summer P in surface waters. The root mean square error (RMSE) for the process-based model, the recurrent neural network, and the PGRNN was 33.0 μg P L -1 , 22.7 μg P L -1 , and 20.7 μg P L -1 , respectively. All models performed better during summer, with RMSE values for the three models (same order) equal to 14.3 μg P L -1 , 10.9 μg P L -1 , and 10.7 μg P L -1 . Although the PGRNN had only marginally better RMSE during summer, it had lower bias and reproduced long-term decreases in lake P missed by the other two models. For all seasons and all years, the recurrent neural network had better predictions than process alone, with root mean square error (RMSE) of 23.8 μg P L -1 and 28.0 μg P L -1 , respectively. The output of PGRNN indicated that new processes related to water temperature, thermal stratification, and long term changes in external loads are needed to improve the process model. By using ecological knowledge, as well as the information content of complex data, PGML shows promise as a technique for accurate prediction in messy, real-world ecological dynamics, while providing valuable information that can improve our understanding of process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advanced electrode processing for lithium-ion battery manufacturing

Lithium-ion batteries (LIBs) need to be manufactured at speed and scale for their use in electric vehicles and devices. However, LIB electrode manufacturing via conventional wet slurry processing is energy-intensive and costly, challenging the goal to achieve sustainable, affordable and facile manufacturing of high-performance LIBs. Here, in this Review, we discuss advanced electrode processing routes (dry processing, radiation curing processing, advanced wet processing and 3D-printing processing) that could reduce energy usage and material waste. Maxwell-type dry processing is a scalable alternative to conventional processing and has relatively low manufacturing cost and energy consumption. Radiation curing processing could enable high-throughput manufacturing, but binder selection is limited to certain radiation curable chemistries. 3D-printing processing can produce electrodes with diverse architectures and improved rate performance, but scalability is yet to be demonstrated. 3D-printing processing is good for special applications where throughput and cost can be compromised for performance.

25 ENERGY STORAGE↗
DOE OSTI2015

MO-F-CAMPUS-T-02: An Electronic Whiteboard Platform to Manage Treatment Planning Process

Purpose: In an effort to improve patient safety and streamline the radiotherapy treatment planning (TP) process, a software based whiteboard had been developed and put in use in our facility Methods: The electronic whiteboard developed using SQL database (DB) and PHP/JavaScript based web interface, is published via department intranet and login credentials. The DB stores data for each TP process such as patient information, plan type, simulation/start dates, physician, dosimetrist, QA and the current status in planning process. Users interact with the DB per plan and perform status updates in real time as the planning process progresses. All user interactions with the DB are recorded with timestamps so as to calculate statistical information for TP process management such as contouring times, planning and review times, dosimetry, physics and therapist QA times. External beam and brachytherapy plans are categorized according to complexity (ex: IMRT, 3D, HDR, LDR etc) and treatment types and applicators. Each plan category is assigned specific timelines for each planning process. When a plan approaches or passes the predetermined timeline, users are alerted via color coded graphical cues. When certain process items are not completed in time, pre-determined actions are triggered such as a delay in treatment start date. Results: Our institution has been using the electronic whiteboard for two years. Implementation of pre-determined actions based on the statistical information collected by the whiteboard improved our TP process. For example, the average time for normal tissue contouring decreased from 0.73±1.37 to 0.24±0.33 days. The average time for target volume contouring decreased from 3.2±2.84 to 2.37±2.54 days. This increase in efficiency allows more time for quality assurance processes, improving patient safety. Conclusion: The electronic whiteboard has been an invaluable tool for streamlining our TP processes. It facilitates timely and accurate communication between all parties involved in the TP process increasing patient safety.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-475: An Evaluation of the Overlap Between the Acceptance Testing and Commissioning Processes for Conventional Medical Linear Accelerators

Purpose: This work’s objective is to determine the overlap of processes, in terms of sub-processes and time, between acceptance testing and commissioning of a conventional medical linear accelerator and to evaluate the time saved by consolidating the two processes. Method: A process map for acceptance testing for medical linear accelerators was created from vendor documentation (Varian and Elekta). Using AAPM TG-106 and inhouse commissioning procedures, a process map was created for commissioning of said accelerators. The time to complete each sub-process in each process map was evaluated. Redundancies in the processes were found and the time spent on each were calculated. Results: Mechanical testing significantly overlaps between the two processes - redundant work here amounts to 9.5 hours. Many beam non-scanning dosimetry tests overlap resulting in another 6 hours of overlap. Beam scanning overlaps somewhat - acceptance tests include evaluating PDDs and multiple profiles but for only one field size while commissioning beam scanning includes multiple field sizes and depths of profiles. This overlap results in another 6 hours of rework. Absolute dosimetry, field outputs, and end to end tests are not done at all in acceptance testing. Finally, all imaging tests done in acceptance are repeated in commissioning, resulting in about 8 hours of rework. The total time overlap between the two processes is about 30 hours. Conclusion: The process mapping done in this study shows that there are no tests done in acceptance testing that are not also recommended to do for commissioning. This results in about 30 hours of redundant work when preparing a conventional linear accelerator for clinical use. Considering these findings in the context of the 5000 linacs in the United states, consolidating acceptance testing and commissioning would have allowed for the treatment of an additional 25000 patients using no additional resources.

60 APPLIED LIFE SCIENCES↗