Results for “utilization plan” — Page 35

NASA NTRS1994

Practical Planning in COLLAGE

COLLAGE is a domain-independent planner that differs from traditional planners in two key ways: (1) it uses a diverse and extendible set of (it action-based) plan constructions methods; and (2) it utilizes a technique called (it localization) to partition the planning problem into smaller (and potentially interacting) sub problems. In this paper, we describe these features and how they are exploited in two different real-world planning domains. The first domain, building construction planning, has served as a framework for us to investigate how localization can improve scalability. The second domain, data analysis planning, benefits from COLLAGE's unique plan construction and representation methods. In addition, we describe extensions that were necessary to tackle these real-world problems.

Lansky, Amy L.↗

NASA NTRS2010

Odor Control Test Plan of the Urine Containment Bag (UCB) for Orion Utilization

The purpose of this test is to evaluate the odor containment of the urine containment bag (UCB), P/N SDD46107234-306 in an environment simulating a spacecraft capsule. The goal is to determine the time of odor break through and the acceptability of the odor, once break through occurs. The goal is to simulate, as close as possible, the volume ratio (trash to free volume), trash content (vomit, urine, feces, and food trash), humidity and temperature of the capsule. The goal for minimum break through is 48 hours (Orion Block 0) from the start of the test. The goal for acceptability of odor is 2 weeks (including docked ISS time for Orion Block 0). Two UCB's will be tested simultaneously in different chambers. The one UCB will be tested empty, serving as a control. Odor break through will be based upon the when the filled UCB total organics exceeds that of the control (empty UCB) by a level detectable by a human panel (approximately 2 ppm).

Casper, Stephanie↗

NASA NTRS2004

The Center Master Plan For NASA Glenn Research Center

The Center Master Plan for NASA Glenn Research Center is a comprehensive survey of NASA Glenn's current facility assets and a vision of how we see the facilities will change over the next 20 years in order to support the changing NASA Mission. This Center Master Plan is a vital management tool used by all organizations for making near term decisions and in future planning. During the summer of 2004, I worked with Joseph Morris, the Chief Architect in the Facilities Division, on beginning this Center Master Planning Process. The previous Master Plan was completed by the Center in 1985 and contained general information on the background of the facility as well as maps detailing environmental and historic records, land use, utilities, etc. The new Master Plan is required for the Center by NASA headquarters and will include similar types of information as used in the past. The new study will provide additional features including showing how individual buildings are linked to the programs and missions that they serve. The Master Plan will show practical future options for the facility s assets with a twenty year look ahead. The Plan will be electronically retrievable so that it becomes a communications tool for Center personnel. A Center Master Plan, although required, is very beneficial to NASA Glenn Research Center in aiding management with the future direction of the campus. Keeping up-to-date information and future plans readily available to all of NASA Glenn will insure that future real property development efficiently and effectively supports the missions camed out and supported by the Center. A Center Master Plan will also facilitate coordination with Center supported programs, stakeholders, and customers. In addition, it will provide a basis for cooperative planning with local and other governmental organizations and ultimately ensure that future budgets include the Center program needs described in the plan. This will ensure that development plans are safe, practical, and cost effective. To properly formulate any future plans, background information and research are required. Before bringing in a consultant to tackle the three year process anticipated to prepare a Center Master Plan, my job was to gather information on different organizations contributions to the NASA mission, their facility needs, consistent trends they observe, etc. I conducted numerous interviews with personnel such as Directorate Representatives, Division Chiefs, Branch Chiefs, System Managers and Building Managers. I documented the information I received from them for future use. I used the information to create various color-coded maps layering the different data. This was done with the ending objective being to collect the information and place it in a database that will be linked with Aperture (a computer program that generates color-coded map layers from database information) and made electronically retrievable to the Planning Consultant, NASA personnel, program stakeholders, and other governmental agencies. My goal this summer was to gather information and ideas appropriate for use in NASA Glenn Research Center s Master Plan and organize them for future application by the Planning Consultant. By the end of the summer, after completion of my goal, I will utilize my knowledge and create an array of preliminary future plans for the facility that can be passed along as a guidance tool.

Bigach, Kristin M.↗

DOE OSTI2015

SU-E-T-303: Dosimetric Comparison of a LINAC Fallback Plan Generated From Tomotherapy System

Purpose: Quantitatively evaluate the Multi Criteria Optimization (MCO) based MLC step and shoot (sMLC) fallback plan derived from Tomotherapy of multiple lesions lung SBRT Methods: Inter-comparison of various IMRT planning systems tends to be difficult due to the vendor-specific functionalities. The methodology of defining dose constraints and beam geometries is challenging. Raysearch™ planning system offers an alternative replanning to deliver same intensity map from Tomotherapy without modifying original fluence. This intuitive comparison comes from the final fluence map converted without any embedded system dependent dose optimization. This planner independent approach could be utilized to study the merits of individual machines. The term “fallback” was utilized to (A) transfer plans in among treatment delivery systems; (B) maintain acceptable plan qualities; and (C) minimize the biological dose impact due to machine breakdown. The Tomotherapy specific DICOM RT dose and plan are retrieved into Raystation’s pre-defined sMLC protocol. Based on specific machine characteristics, same fluence maps were converted to generate equivalent deliverable segments. Therefore, the treatment plans were evaluated among two planning tools, Tomotherapy and MCO based sMLC delivery plans. Results: By converting the fluence map with the pre-defined machine characteristics, the 9-fields fallback plan has similar ITV coverage compared to the original Tomotherapy plan. ITV average doses, the D95 consisted of 0.9% variation. The total lung doses of fallback plan drifted from 17.4% to 30.5% which represents the limitations of the static beam delivery. D2 of fallback spinal cord increased from 22.4% to 36.4% but still within tolerances. Ipsilateral lung changed from 11.0% to 22.6%. Low dose region between ITVs presented increased dose to the normal lung tissues. Conclusion: Acceptable fallback plan for Tomotherapy SBRT has similar ITVs coverage, but lack of the normal tissues avoidance due to the limitation of geometrical factors to reduce doses in between ITVs.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Weathering the Worst Solar Storms

When the last really big solar storm hit in 1921, Earth’s magnetic field funneled a wave of electrically charged particles toward the ground, where they induced a current along telegraph lines and railroad tracks, setting to telegraph offices and train stations—and the fledgling electric grid went dark. Almost a century later, today’s grid is bigger, more interconnected, and even more susceptible to a solar storm disaster. Los Alamos National Laboratory is developing a scientific analysis about how frequently a major geomagnetic storm might strike, which regions of the country are most vulnerable, and how bad it might be. This analysis is part of a plan to support electric utility companies and government regulators in taking the necessary steps to spare us all from the nightmare of days, weeks, or even months without power.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1979

Solar thermal power plants in small utilities - An economic impact analysis

A study was performed to assess the potential economic impact of small solar thermal electric power systems in statistically representative synthetic small utilities of the Southwestern United States. Power supply expansion plans were compared on the basis of present worth of future revenue requirements for 1980-2000 with and without solar thermal plants. Coal-fired and oil-fired municipal utility expansion plans with 5 percent solar penetration were 0.5 percent and 2.25 percent less expensive, respectively, than the corresponding conventional plan. At $969/kWe, which assumes the same low cost solar equipment but no improvement in site development costs, solar penetration of 5 percent in the oil-fired municipal reduced revenue requirements 0.88 percent. The paper concludes that some solar thermal plants are potentially economic in small community utilities of the Southwest.

Bluhm, S. A.↗

DOE OSTI2014

SU-E-T-31: Alternative VMAT Technique Reduces Total Monitor Units for Lung SBRT

Purpose: To investigate an alternative approach to VMAT optimization for hypofractionation lung treatment which increases average aperture opening and results in lower total Monitor Units (MU) without significantly sacrificing plan quality. Methods: Benchmark Volumetric Modulated Arc Therapy (bVMAT) plans were generated for 10 lung Stereotactic Body radiotherapy (SBRT) cases using Eclipse Version 11.0.42 (Varian Medical Systems) without a maximum MU constraint. Prescriptions ranged from 40 to 54Gy in 3 to 5 fractions. AAA dose calculation and PRO fluence based optimization was utilized. Two comparison VMAT plans were generated for each case, one that forced an initial “open” mlc aperture conformal to the tumor as a starting condition (oVMAT) with similar optimization parameters and arc geometries, and one that repeated the bVMAT optimization but added a maximum MU constraint (muVMAT). All plans used two arcs with lengths between 168 to 230 degrees. PTV D 95% and Dmean, lung V20 Gy, chest wall V30 Gy, average aperture opening and MU's were compared. Statistical significance was evaluated using Wilcoxon signed rank test. Results: Average PTV D(95), PTV mean and lung V20Gy over all plans was 99.2 ± 1.7%, 103.3 ± 0.6% and 7.8 ± 2.4% respectively. The average chest wall V30Gy was 61 ± 61 cc and ranged between 0 to 166 cc. There were no significant differences between the three techniques for the dosimetric quantities. MUs were reduced by 11 ±11% (p<0.01) and 25 ± 5% (p<0.01) and the average aperture size was increased by 13.7 ± 14% (p=0.02) and 35.8 ± 10% (p<0.01) with muVMAT and oVMAT, respectively, compared to bVMAT. Conclusion: oVMAT and muVMAT techniques were both able to increase average aperture size and reduce total MU compared to the benchmark VMAT plan, but the magnitude of the changes observed for oVMAT was larger.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-P-07: Applying Failure Modes and Effects Analysis to Treatment Planning System QA

Purpose: A small-scale implementation of Failure Modes and Effects Analysis (FMEA) for treatment planning system QA by utilizing methodology of AAPM TG-100 report. Methods: FMEA requires numerical values for severity (S), occurrence (O) and detectability (D) of each mode of failure. The product of these three values gives a risk priority number (RPN). We have implemented FMEA for the treatment planning system (TPS) QA for two clinics which use Pinnacle and Eclipse TPS. Quantitative monthly QA data dating back to 4 years for Pinnacle and 1 year for Eclipse have been used to determine values for severity (deviations from predetermined doses at points or volumes), and occurrence of such deviations. The TPS QA protocol includes a phantom containing solid water and lung- and bone-equivalent heterogeneities. Photon and electron plans have been evaluated in both systems. The dose values at multiple distinct points of interest (POI) within the solid water, lung, and bone-equivalent slabs, as well as mean doses to several volumes of interest (VOI), have been re-calculated monthly using the available algorithms. Results: The computed doses vary slightly month-over-month. There have been more significant deviations following software upgrades, especially if the upgrade involved re-modeling of the beams. TG-100 guidance and the data presented here suggest an occurrence (O) of 2 depending on the frequency of re-commissioning the beams, severity (S) of 3, and detectability (D) of 2, giving an RPN of 12. Conclusion: Computerized treatment planning systems could pose a risk due to dosimetric errors and suboptimal treatment plans. The FMEA analysis presented here suggests that TPS QA should immediately follow software upgrades, but does not need to be performed every month.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1985

Computer simulation of environmental, hazard scenarios in space

The development of the Advanced Computer Graphics Laboratory at NASA/JSC will enable NASA engineers to utilize state-of-the-art computer systems to simulate and analyze current and planned space missions. These systems utilize computer graphics to animate automated satellite rendezvous and docking, satellite servicing, tether operations, as well as remote manipulator activities and assembly of large space structures including the space station. These computer simulations enhance the engineering evaluation of possible hazardous scenarios in space by allowing users to view from any point in space these activities and determine if any potential problem could occur.

Brown, R. H.↗

DOE OSTI2022

An Analysis of PNM's Renewable Reserve Requirements to Meet New Mexico's Decarbonization Goals

Over the next three years, the Public Service Company of New Mexico (PNM) plans to increase utility-scale solar photovoltaic (PV) capacity from today’s roughly 330MW to about 1600MW. This massive increase in variable generation—from about 15% to 75% of peak load—will require changes in how PNM operates their system. We characterize the 5 and 30-minute solar and wind forecast errors that the system is likely to experience in order to determine the level of reserves needed to counteract such events. Our focus in this study is on negative forecast error (in other words, shortfalls relative to forecast) – whereas excess variable generation can be curtailed if needed, a shortfall must be compensated for to avoid loss of load. Calculating forecast error requires the use of the same forecasting methods that PNM uses or a reasonable approximation thereof. For wind, we use a persistence forecast on actual 5-minute 2019 wind output data (scaled up to reflect the amount of wind capacity planned for 2025). For solar, we use a formula incorporating the clear sky index (CSI) for the forecast. As the solar on the grid now is a small fraction of what is planned for 2025, we generated 5-minute solar data using 2019 weather inputs. We find that to handle 99.9% of the 5-minute negative forecast errors, a maximum of 275MW of variable generation reserve during daylight hours, and a maximum of 75MW during non-daylight hours, should be sufficient. Note that this variable generation reserve is an additional reserve category that specifies reserves over and above what are currently carried for contingency reserve. This would require a significant increase in reserve relative to what PNM currently carries or can call upon from other utilities per reserve sharing agreements. This variable generation reserve specification may overestimate the actual level needed to deal with PNM’s planned variable generation in 2025. The forecasting methodologies used in this study likely underperform PNM’s forecasting – and better forecasting allows for less reserve. To obtain more precise estimates, it is necessary to consider load and use the same forecasting inputs and methods used by PNM.

14 SOLAR ENERGY↗

DOE OSTI2013

Planning Tool for Strategic Evaluation of Facility Plans - 13570

Savannah River National Laboratory (SRNL) has developed a strategic planning tool for the evaluation of the utilization of its unique resources for processing and research and development of nuclear materials. The Planning Tool is a strategic level tool for assessing multiple missions that could be conducted utilizing the SRNL facilities and showcasing the plan. Traditional approaches using standard scheduling tools and laying out a strategy on paper tended to be labor intensive and offered either a limited or cluttered view for visualizing and communicating results. A tool that can assess the process throughput, duration, and utilization of the facility was needed. SRNL teamed with Newport News Shipbuilding (NNS), a division of Huntington Ingalls Industries, to create the next generation Planning Tool. The goal of this collaboration was to create a simulation based tool that allows for quick evaluation of strategies with respect to new or changing missions, and clearly communicates results to the decision makers. This tool has been built upon a mature modeling and simulation software previously developed by NNS. The Planning Tool provides a forum for capturing dependencies, constraints, activity flows, and variable factors. It is also a platform for quickly evaluating multiple mission scenarios, dynamically adding/updating scenarios, generating multiple views for evaluating/communicating results, and understanding where there are areas of risks and opportunities with respect to capacity. The Planning Tool that has been developed is useful in that it presents a clear visual plan for the missions at the Savannah River Site (SRS). It not only assists in communicating the plans to SRS corporate management, but also allows the area stakeholders a visual look at the future plans for SRS. The design of this tool makes it easily deployable to other facility and mission planning endeavors. (authors)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A Review of Resilience and Long-Term Planning in Power and Water Systems in the United States

There is recognition among power and water utilities that the frequency and magnitude of high consequence and low probability events could increase as a result of climate change. The interconnected nature of energy-water systems raises the possibility of cascading failures, increasing complexity and risks. Resilience and long-term planning are important ways of weathering the effects of climate change. First, to understand more about resilience, we reviewed existing literature on resilience definitions, metrics, and modeling, focusing on integrated water-power systems. Second, to understand how resilience and planning are being applied in practice, we interviewed utilities and organized, curated, and synthesized the interview data to arrive at several key findings, which are presented here. We found that there is not a consistent definition for resilience, yet it is something that utilities regularly plan for, often with different names and varying methods/measures. However, there is a tangible shift in the industry towards defining and determining measurable resilience metrics. While the exact metrics are a work in progress, utilities are taking steps forward by (1) putting people and culture at the center of resilience, (2) recognizing their own interdependencies, and (3) pursuing better cross-sector collaboration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

SU-F-T-635: Lung SBRT: Dosimetric and Treatment Time Comparison of Volumetric-Modulated Arc Therapy and Three-Dimensional Conformal Radiotherapy in Clinically Treated Cases

Purpose: To compare three-dimensional conformal radiotherapy (3D CRT) and volumetric-modulated arc therapy (VMAT) in lung stereotactic body radiation therapy (SBRT) Methods: A retrospective study of clinically treated lung SBRT cases treated between 2010 and 2015 at our hospital was performed. All treatment modalities were included in this evaluation (VMAT, 3D CRT, static IMRT, and dynamic conformal arc therapy). However, the majority of treatment modalities were either VMAT or 3D CRT. Treatment times of patients and dosimetric plan quality metrics were compared. Treatment times were calculated based on the time the therapist opened and closed the patient’s treatment plan. This treatment time closely approximates the utilization time of the treatment room. The dosimetric plan quality metrics evaluated include ICRU conformity index, the volume of 105% prescribed dose outside PTV, the ratio of volume of 50% prescribed dose to the volume of PTV, the percentage of maximum dose at 2 cm away from PTV to the prescribed dose, and the V20 (percentage of lung volume receiving 20 Gy or more). Results: Treatment time comparisons show that on average VMAT has shorter treatment times than 3D CRT. Dose conformity, defined by the ICRU conformity index, and high dose spillage, defined by the volume of 105% dose outside the PTV, is reduced when using VMAT compared to 3D CRT. V20 and intermediate dose spillage/fall-off metrics of VMAT and 3D are not significantly different. Conclusion: Clinically treated lung SBRT cases indicate VMAT is superior to 3D with regard to shorter treatment times, plan dose conformity, and plan high dose spillage.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-BRB-00: New Developments in Knowledge-Based Treatment Planning and Automation

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-BRB-01: The Power of Ontologies and Standardized Terminologies for Capturing Clinical Knowledge

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-BRB-02: Setting the Stage for Incorporation of Toxicity Measures in Treatment Plan Assessments

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-BRB-03: Inclusion of Data-Driven Risk Predictions in Radiation Treatment Planning in the Context of a Local Level Learning Health System

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

A Guide for Creating a Building-Level Action Plan to Improve Energy Efficiency and Reduce Carbon Emissions

Action plans are tools for commercial building owners to create pathways for reducing energy use and decarbonize, hence reducing carbon emissions. This template and associated direction manual provides a method for creating an action plan. Originally created for the Better Buildings Low Carbon Pilot, it can also be applied to the Better Buildings Climate Challenge and for any building owner striving towards lower carbon footprints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗