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MAUS: the MICE analysis user software

The Muon Ionization Cooling Experiment (MICE) collaboration has developed the MICE Analysis User Software (MAUS) to simulate and analyze experimental data. It serves as the primary codebase for the experiment, providing for offline batch simulation and reconstruction as well as online data quality checks. The software provides both traditional particle-physics functionalities such as track reconstruction and particle identification, and accelerator physics functions, such as calculating transfer matrices and emittances. The code design is object orientated, but has a top-level structure based on the Map-Reduce model. This allows for parallelization to support live data reconstruction during data-taking operations. MAUS allows users to develop in either Python or C++ and provides APIs for both. Various software engineering practices from industry are also used to ensure correct and maintainable code, including style, unit and integration tests, continuous integration and load testing, code reviews, and distributed version control. The software framework and the simulation and reconstruction capabilities are described.

47 OTHER INSTRUMENTATION↗

Implementing a Hardware Testbed Using 3-Level ANPC Software Defined Inverters for Fault Analysis of a Transmission Network

In this paper, we propose the implementation of a hardware testbed using 3-level active neutral point clamped (ANPC) software-defined inverters for fault analysis. A test case transmission network equipped with two grid forming (GFM) inverters and four resistive loads is considered in this research. Firstly, grid forming control laws including PI feedback control and droop control are implemented to operate the inverters in parallel. Then, we implement a fault ride-through (FRT) logic and perform a simulation of the test system by applying a three-phase fault. Simulation results show the effectiveness of the fault recovery algorithm upon clearance of the fault. Finally, a 3-level ANPC software-defined inverter is programmed with required control laws and characterized through various lab experiments.

3-level ANPC inverter↗

Operationalizing Synchrophasors for Enhanced Grid Reliability and Asset Utilization

The report discusses the development of production-grade synchrophasor software applications. The objective is to improve system reliability and asset utilization for offline as well as real-time considerations, as per the Department of Energy (DOE) guidelines specified by Funding Opportunity Announcement (FOA) DE-FOA-0001492. On the one hand, we have developed grid management applications on how to transform synchrophasor-based monitoring into operator guidance, and commercial grade tools addressing industry needs such as NERC Reliability Standards (MOD 26, MOD 27 and MOD 33). On the other hand, with the wide industrial adoption in mind, the developed applications have been fully discussed with utility partners and installed in the utility partners site including 6 field tests. The Model Validation and Calibration software module has been integrated into GE’s PhasorAnalyticsTM. The first commercial contract has been signed even before the close date of this project. The Angle-based Grid Management (AGM), Fast Voltage Security Assessment (FastVSA), Enhanced Islanding Monitoring(EIM) and Enhanced Disturbance Management (EDM) have been integrated into GE’s Grid Stability Assessment line of applications in e-terra Suite of EMS product.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NRC technical basis for evaluation of its position on protection against common cause failure in digital systems used in nuclear power plants - 378

Digital technology has advantages over analog systems, including automated monitoring and alerts for standby safety functions, and predictive algorithms to maintain critical safety systems. Additionally, digital technology generally has higher reliability and can be designed to reduce single point vulnerabilities. For these reasons many nuclear plants have applied digital technology to safety and non-safety related applications, including reactor protection system, feedwater and turbine controls, etc. with a corresponding significant improvement in trip reduction. Nonetheless, digital instrumentation and control (I and C) systems also present potential new vulnerabilities that need to be assessed, including potential failures due to increased complexity of digital systems, the introduction of unique failure modes due to software (including software common cause failure (CCF)), and limited operating history of digital systems in nuclear safety related applications compared to analog systems. The fact that software is intangible means that common methods, such as analysis or testing, used for detecting CCF may not be effective when applied to software. Consequently, digital technology is perceived to pose a potential risk from the introduction of undetected systematic faults that could result in CCF. Despite the I and C system upgrades and modifications performed to date, the U.S. Nuclear Regulatory Commission (NRC) and industry stakeholders have identified the need to modernize the regulatory infrastructure to efficiently address risks associated with the use of digital technology for nuclear safety applications and address regulatory uncertainties. The NRC's current position on CCF is guided by the staff requirements memorandum (SRM) on SECY 93-087. The SRM provides specific acceptance criteria for the evaluation of CCF, which the staff implemented in the Branch Technical Position (BTP) 7-19. However, industry stakeholders have proposed using methods to characterize the likelihood of software CCF and eliminate it from further consideration in a defense-in-depth and diversity analysis. The NRC's current position does not consider these alternatives, and thus corresponding acceptance criteria is not currently available. The work discussed in this paper assesses the underlying technical basis associated with CCF, provides technical support for updating the NRC position and considers proposed methods for addressing potential CCF in digital systems while enhancing efficiency, clarity, and confidence. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Conversion and Validation of Distribution System Model from a QSTS-Based Tool to a Real-Time Dynamic Phasor Simulator

A software process is developed to convert distribution network models from a quasi-static time-series tool (OpenDSS) to a real-time dynamic phasor simulator (ePHASORSIM). The description of this process in this paper would be helpful for researchers who intend to perform similar conversions. The converter could be utilized directly by users of real-time simulators who intend to perform software-in-the-loop or hardware-in-the-loop tests on large distribution test feeders for a range of use cases, including testing functions of advanced distribution management systems against a simulated distribution system. In the future, the developers intend to release the conversion tool as open source to enable use by others.

24 POWER TRANSMISSION AND DISTRIBUTION↗

QXF Cold Mass Friction Test

The purpose of this test is to determine the longitudinal force on the stainless steel shell that is required to break the friction between the stainless steel shell and the aluminum shell underneath. This is achieved by suspending the short magnet between two backing plates on the eight grade 8 threaded rods which replace the 8 stainless steel toke tie rods in the magnet assembly. Eight hydraulic cylinders are mounted to each backing plate. Six, 22" sections of the stainless steel shell are welded in place on the magnet, each of which has a slightly different developed length, starting from the baseline design, and becoming progressively looser. A pushing flange is mounted to the stainless steel shells via small tack welds. Four load cells are then attached to the flange at designated points, while additional tooling is attached to each of the cylinders to facilitate the transfer of force from the cylinders to the stainless steel shell During the test, the cylinders will be slowly energized to no more than 7000 psi, with a resultant, longitudinal force on the flange of no more than 125,400 lbf. For each set of shells, the test ends when the load cell monitoring software detects a sharp decrease in force. This will indicate that the friction has broken. The cullenders will then be de-energized and the cycle will repeat for the next test. Welding operations outlined in the procedure (US-HiLumi-doc-4200) are outside the scope of the HA as the work is occurring under a previously-issued burn permit by qualified welders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗

Subtask 2.18 - Advancing CO 2 Capture Technology: Partnership for CO 2 Capture (PCO 2 C) Phase III

Industries and utilities continue to investigate ways to decrease their carbon footprint. Carbon capture and storage (CCS) can enable existing power generation facilities to meet the current national CO 2 reduction goals. The Partnership for CO2 Capture Phase III focused on several important research areas in an effort to find ways to decrease the cost of capture across both precombustion and postcombustion platforms. Two flue gas pretreatment technologies for postcombustion capture, an SO 2 reduction scrubbing technology from Cansolv Technologies Inc. and the Tri-Mer filtration technology that combines particulate, NOx, and SO 2 control, were evaluated on the Energy & Environmental Research Center’s (EERC’s) pilot-scale test system. Pretreating the flue gas should enable more efficient, and therefore less expensive, CO 2 capture. Both technologies were found to be effective in pretreating flue gas prior to CO 2 capture. Two new postcombustion capture solvents were tested, one from the Korea Carbon Capture and Sequestration R&D Center (KCRC) and one from CO 2 Solutions Incorporated. Both of these solvents showed the ability to capture CO 2 while requiring less regeneration energy, which would reduce the cost of capture. Hydrogen separation membranes from Commonwealth Scientific and Industrial Research Organisation were evaluated through precombustion testing. They are composed of vanadium alloy, which is less expensive than the palladium alloys that are typically used. Their performance was comparable to that of other membranes that have been tested at the EERC. Aspen Plus® software was used to model the KCRC and CO 2 Solutions solvents and found that they would result in significantly improved overall plant performance. The modeling effort also showed that the parasitic steam load at partial capture of 45% is less than half that of 90% overall capture, indicating savings that could be accrued if 90% capture is not required. Modeling of three regional power plants using the Carnegie Mellon Integrated Environmental Control Model showed that, among other things, the use of a bypass during partial capture may minimize the size of the capture tower(s) and result in a slight reduction in the revenue required to operate the capture facility. The results reinforced that a one-size-fits-all approach cannot be taken to adding capture to a power plant. Laboratory testing indicated that Fourier transform infrared spectroscopy could be used to continuously sample stack emissions at CO 2 capture facilities to detect and quantify any residual amine or its degradation products, particularly nitrosamines. The information gathered during Phase III is important for utility stakeholders as they determine how to reduce their CO 2 emissions in a carbon-constrained world. This subtask was funded through the EERC–U.S. Department of Energy (DOE) Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FC26-08NT43291. Nonfederal funding was provided by the North Dakota Industrial Commission, PPL Montana, Nebraska Public Power District, Tri-Mer Corporation, Montana–Dakota Utilities Co., Basin Electric Power Cooperative, KCRC/Korean Institute of Energy Research, Cansolv Technologies, and CO 2 Solutions, Inc.

01 COAL, LIGNITE, AND PEAT↗

Characterization and operation optimization of large aperture optical interferometers using binary pseudorandom array test standards

Recently, a technique for calibration of the Modulation Transfer Function (MTF) of a broad variety of metrology instrumentation has been established. The technique is based on test samples structured according to binary pseudorandom (BPR) one-dimensional sequences and two-dimensional arrays. The inherent power spectral density of BPR gratings and arrays, has a deterministic white-noise-like character that allows a direct determination of the MTF with a uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. As such, the BPR samples satisfy the characteristics of a test standard: Functionality, ease of specification and fabrication, reproducibility, and low sensitivity to manufacturing error. Here we discuss our recent developments working with support of the U.S. Department of Energy on industrialization of the technique. The goal is to develop affordable BPR test samples, application procedures, and data processing software, suitable for thorough characterization of optical interferometers and microscopes, as well as x-ray, electron (scanning and transmission), and atomic force microscopes. We report on the development of BPR array test samples optimized for advanced characterization (including the instrumental MTF and aberrations) and operation optimization of large aperture optical interferometers. We describe the sample fabrication process and tests to verify the compliance to desired surface topography. The data acquisition and analysis procedures for application of the technique for precise focusing of Fizeau interferometer are discussed in detail.

Yashchuk, VV↗

Development of advanced manufacturing technologies for low cost hydrogen storage vessels

The U.S. Department of Energy (DOE) defined a need for low-cost gaseous hydrogen storage vessels at 700 bar to support cost goals aimed at 500,000 units per year. Existing filament winding processes produce a pressure vessel that is structurally inefficient, requiring more carbon fiber for manufacturing reasons, than would otherwise be necessary. Carbon fiber is the greatest cost driver in building a hydrogen pressure vessel. The objective of this project is to develop new methods for manufacturing Type IV pressure vessels for hydrogen storage with the purpose of lowering the overall product cost through an innovative hybrid process of optimizing composite usage by combining traditional filament winding (FW) and advanced fiber placement (AFP) techniques. A numbers of vessels were manufactured in this project. The latest vessel design passed all the critical tests on the hybrid design per European Commission (EC) 79-2009 standard except the extreme temperature cycle test. The tests passed include burst test, cycle test, accelerated stress rupture test and drop test. It was discovered the location where AFP and FW overlap for load transfer could be weakened during hydraulic cycling at 85°C. To design a vessel that passed these tests, the in-house modeling software was updated to add capability to start and stop fiber layers to simulate the AFP process. The original in-house software was developed for filament winding only. Alternative fiber was also investigated in this project, but the added mass impacted the vessel cost negatively due to the lower performance from the alternative fiber. Overall the project was a success to show the hybrid design is a viable solution to reduce fiber usage, thus driving down the cost of fuel storage vessels. Based on DOE’s baseline vessel size of 147.3L and 91kg, the 129L vessel (scaled to DOE baseline) in this project shows a 32% composite savings and 20% cost savings when comparing Vessel 15 hybrid design and the Quantum baseline all filament wound vessel. Due to project timing, there was no additional time available to fine tune the design to improve the load transfer between AFP and FW. Further design modifications will likely help pass the extreme temperature cycle test, the remaining test that is critical to the hybrid design.

08 HYDROGEN↗

Substation Secondary Asset Health Monitoring and Management System (SSHM)

Electric Power Group, LLC (EPG) was awarded DOE OE0000850 to design, develop, and demonstrate a real-time software application for substation secondary equipment health monitoring and management at host utility American Electric Power (AEP), a cost share partner. This project addresses the need for monitoring substation equipment health and providing operators with tools to identify and take pre-emptive action to avoid catastrophic equipment failure. By monitoring synchrophasor data in real time, data anomalies that indicate potential asset failure can be detected and alerts can be sent to operators in time to take corrective actions. EPG developed two data driven algorithms to identify abnormal equipment signature patterns as well as a method using substation linear state estimation (SLSE). The software has been deployed on hardened PC’s and tested and validated for cost share partner AEP’s substations - 138kV and 765 kV. The SSHM software has been accepted by AEP and final demonstration of DOE - OE0000850 for AEP and DOE was successfully completed on March 17th, 2020. EPG developed the Substation Secondary Asset Health Monitoring (SSHM) Platform to analyze equipment failure signatures in PMU data and alert substation personnel when pre-emptive inspection, repairs and other actions are warranted to prevent potential catastrophic failures. This is the first system that automatically monitors the health of substation secondary assets and alerts users to emerging failures using synchrophasor measurements. SSHM uses high resolution PMU data from PTs, CTs, and CCVTs to analyze equipment signatures and identify anomalies that are precursor indicators of potential equipment failure. When an anomaly is detected, there is a likelihood of potential failure of monitored equipment, the system alerts the user with visual alarms including alarm trend charts and indicator lights on a oneline diagram of the substation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NREL Controllable Grid Interface for Testing MW-Scale Wind Turbine Generators (Poster)

In order to understand the behavior of wind turbines experiencing grid disturbances, it is necessary to perform a series of tests and accurate transient simulation studies. The latest edition of the IEC 61400-21 standard describes methods for such tests that include low voltage ride-through (LVRT), active power set-point control, ramp rate limitations, and reactive power capability tests. The IEC methods are being widely adopted on both national and international levels by wind turbine manufacturers, certification authorities, and utilities. On-site testing of wind turbines might be expensive and time consuming since it requires both test equipment transportation and personnel presence in sometimes remote locations for significant periods of time because such tests need to be conducted at certain wind speed and grid conditions. Changes in turbine control software or design modifications may require redoing of all tests. Significant cost and test-time reduction can be achieved if these tests are conducted in controlled laboratory environments that replicate grid disturbances and simulation of wind turbine interactions with power systems. Such testing capability does not exist in the United States today. An initiative by NREL to design and construct a 7-MVA grid simulator to operate with the existing 2.5 MW and new upcoming 5-MW dynamometer facilities will fulfill this role and bring many potential benefits to the U.S. wind industry with the ultimate goal of reducing wind energy integration costs.

17 WIND ENERGY↗

Practical Insights on Applying Simulation-Based Control Methods in Experimental Studies

Advanced nuclear reactors are crucial to the future of energy both in the United States and around the globe. In contrast to the current operating fleet, they are characterized as being deployable in remote locations and able to operate in semi-autonomous or autonomous fashion. This leap forward necessitates a new reactor control paradigm. Because advanced nuclear reactors are still under development in the United States, the creation of new control methods to achieve autonomous operations has been based on systems modeling and simulation. However, an important factor in successfully deploying these new control methods is the ability to seamlessly transition from simulation environments to real-world settings. Control methods tested in both simulation and experimental settings need to be investigated in the context of advanced reactor applications. This work developed a series of simple controllers for Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor operating in load-following scenarios. These controllers were tested in both simulation and experimental settings, and a comparative performance analysis was performed. The simulation tests leveraged the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software developed in a previous stage of the current effort, along with the MARVEL Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The experimental tests leveraged the COMMAND software, MARVEL models, and the U.S. Department of Energy Microreactor Program’s Microreactor Automated Control System (MACS). MACS was developed to serve as a control method testbed. It was customized to mirror the MARVEL microreactor, and COMMAND enabled MACS to emulate the physics of MARVEL. The load-following controller was developed using the simulation platform, with efforts to emulate real systems by introducing actuator saturation and noise. These factors were incrementally accounted for in the controller design. After finalizing the controller design, it was implemented with the experimental setup. The experimental conditions tested included an initial test under conditions similar to the final simulation test, and two additional scenarios. The first scenario introduced additional actuator saturation to account for equipment aging over time, which was unknown to the controller. The second scenario introduced sensor delay, a phenomenon anticipated with the use of remote operations or wireless communication in advanced reactors. These tests revealed several notable differences. While the controller performed well in simulation, it exhibited several limitations when transitioning to hardware. The main challenges involved maintaining the steady-state target power, as evidenced by larger error values between the true reactor power and setpoint power, as well as persistent oscillations in controlled reactor power. These issues could lead to unacceptable transient conditions in real reactor testing. Introducing actuator aging and stochastic delays in the experimental setup significantly impacted controller performance, resulting in increased overshoot and undershoot, and exacerbated error and oscillations previously mentioned. These findings underscore the importance of experimental testbeds for testing and validating control methods, as controllers developed using only theory and/or simulation may perform unexpectedly when applied to actual hardware. This research emphasizes the need for an experimental testbed for achieving such validation.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Modernising ATLAS Software Build Infrastructure

In the last year ATLAS has radically updated its software development infrastructure hugely reducing the complexity of building releases and greatly improving build speed, flexibility and code testing. The first step in this transition was the adoption of CMake as the software build system over the older CMT. This required the development of an automated translation from the old system to the new, followed by extensive testing and improvements. This resulted in a far more standard build process that was married to the method of building ATLAS software as a series of 12 separate projects from Subversion. We then proceeded with a migration of the code base from Subversion to Git. As the Subversion repository had been structured to manage each package more or less independently there was no simple mapping that could be used to manage the migration into Git. Instead a specialist set of scripts that captured the software changes across official software releases was developed. With some clean up of the repository and the policy of only migrating packages in production releases, we managed to reduce the repository size from 62 GiB to 220 MiB. After moving to Git we took the opportunity to introduce continuous integration so that now each code change from developers is built and tested before being approved. With both CMake and Git in place we also dramatically simplified the build management of ATLAS software. Many heavyweight homegrown tools were dropped and the build procedure was reduced to a single bootstrap of some external packages, followed by a full build of the rest of the stack. This has reduced the time for a build by a factor of 2. It is now easy to build ATLAS software, freeing developers to test compile intrusive changes or new platform ports with ease. We have also developed a system to build lightweight ATLAS releases, for simulation, analysis or physics derivations which can be built from the same branch.

97 MATHEMATICS AND COMPUTING↗

Testing convolutional neural network based deep learning systems: a statistical metamorphic approach

Machine learning technology spans many areas and today plays a significant role in addressing a wide range of problems in critical domains,i.e., healthcare, autonomous driving, finance, manufacturing, cybersecurity,etc. Metamorphic testing (MT) is considered a simple but very powerful approach in testing such computationally complex systems for which either an oracle is not available or is available but difficult to apply. Conventional metamorphic testing techniques have certain limitations in verifying deep learning-based models (i.e., convolutional neural networks (CNNs)) that have a stochastic nature (because of randomly initializing the network weights) in their training. In this article, we attempt to address this problem by using a statistical metamorphic testing (SMT) technique that does not require software testers to worry about fixing the random seeds (to get deterministic results) to verify the metamorphic relations (MRs). We propose seven MRs combined with different statistical methods to statistically verify whether the program under test adheres to the relation(s) specified in the MR(s). We further use mutation testing techniques to show the usefulness of the proposed approach in the healthcare space and test two CNN-based deep learning models (used for pneumonia detection among patients). The empirical results show that our proposed approach uncovers 85.71% of the implementation faults in the classifiers under test (CUT). Furthermore, we also propose an MRs minimization algorithm for the CUT, thus saving computational costs and organizational testing resources.

Computer Science↗

Requirements for Cataloging Hanford Geophysical Datasets

Environmental management activities at the Hanford Site produce extensive data about site conditions, contaminants, cleanup, and more. Managing and archiving that data requires a high degree of collaboration among site contractors and a high level of awareness by project managers and staff. Part of that effort is developing a Hanford Environmental Information and Data Index (HEIDI) to organize the data and maximize its value by making it findable and available for reuse. The objective is to catalog the disparate data sets collected to address the evolving needs of planning, executing, and documenting cleanup over several decades up to the present day, including links to active data sources when available. A properly implemented data catalog makes finding environmental datasets related to an area or theme a routine, reliable process, without requiring the searcher to have special knowledge that a data set exists and where it may be stored. In this project, a working group, including the U.S. Department of Energy, the Hanford Site contractors, and Pacific Northwest National Laboratory staff, identified needs and requirements for handling complex site data. Geophysical data was chosen as a test case because it can be large and complex and often involves multiple processing steps to extract the information incorporated into deliverables. The ability to document those steps was one of the requirements identified for the catalog. In addition to developing requirements, other activities included selecting a metadata schema and initial testing with the objective of determining whether the workflow and capabilities of selected data catalog software platforms were sufficient to implement and impose the identified requirements. This initial testing involved running the default catalog instance using the software platform of interest and altering the configuration to achieve each requirement, if possible. Where configuration alone was insufficient, the possibility of modifying the software by changing the code was examined, but not implemented. A follow-on task is planned to reprogram the code as necessary to implement requirements in a prototype catalog.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

RELAP5-3D Developer Guidelines and Programming Practices

Our ultimate goal is to create and maintain RELAP5-3D as the best software tool available to analyze nuclear power plants. This begins with writing excellent programming and requires thorough testing. This document covers development of RELAP5-3D software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SU-E-P-43: A Knowledge Based Approach to Guidelines for Software Safety

Purpose: In the fall of 2012, a survey was distributed to medical physicists across Canada. The survey asked the respondents to comment on various aspects of software development and use in their clinic. The survey revealed that most centers employ locally produced (in-house) software of some kind. The respondents also indicated an interest in having software guidelines, but cautioned that the realities of cancer clinics include variations, that preclude a simple solution. Traditional guidelines typically involve periodically repeating a set of prescribed tests with defined tolerance limits. However, applying a similar formula to software is problematic since it assumes that the users have a perfect knowledge of how and when to apply the software and that if the software operates correctly under one set of conditions it will operate correctly under all conditions Methods: In the approach presented here the personnel involved with the software are included as an integral part of the system. Activities performed to improve the safety of the software are done with both software and people in mind. A learning oriented approach is taken, following the premise that the best approach to safety is increasing the understanding of those associated with the use or development of the software. Results: The software guidance document is organized by areas of knowledge related to use and development of software. The categories include: knowledge of the underlying algorithm and its limitations; knowledge of the operation of the software, such as input values, parameters, error messages, and interpretation of output; and knowledge of the environment for the software including both data and users. Conclusion: We propose a new approach to developing guidelines which is based on acquiring knowledge-rather than performing tests. The ultimate goal is to provide robust software guidelines which will be practical and effective.

60 APPLIED LIFE SCIENCES↗