Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “scorecard”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

41 records · Page 3

Flight Mechanics Modeling and Simulation of the Earth Entry System

Introduction: The Mars Sample Return (MSR) Campaign being planned by NASA and ESA has the ambitious goal to return Mars samples back to Earth. This international collaboration had developed a concept of operations that included a ESA-designed Earth Return Orbiter (ERO) and NASA-designed Capture, Containment, and Return System (CCRS). The Earth Entry System (EES), consisting of a protective aeroshell that houses the samples as well as sample containment vessels, would conduct entry, descent, and landing (EDL) on a direct Earth trajectory. The EES would enter on a spin-stabilized ballistic trajectory with the goal to passively achieve aerodynamic stability throughout all regions of flight. The EDL sequence would end with the EES impacting the soft playa soil of the Utah Test and Training Range (UTTR). As of the submission of this abstract, the MSR campaign is undergoing a re-architecture leading to a pause in EES development. However, the novel approaches developed in flight mechanics modeling and simulation can significantly benefit the greater IPPW community in the development of Earth return vehicles. This paper will present the latest state of EES flight mechanics modeling and simulation. The paper will highlight the simulation architecture developed and key lessons learned from understanding of EDL trajectory sensitivities. Modeling and Simulation: Figure 1 provides a high-level concept of operations for the approach, entry, descent, and landing (AEDL) phase of the CCRS-portion of MSR. The objective of EES flight mechanics is to model and simulate the EES trajectory from ERO separation to ground impact at UTTR. A variety of flight mechanics simulation models were utilized to model both exo-atmopsheric and atmospheric portions of flight. 42, a 6-DOF simulation developed at Goddard Space Flight Center, is utilized for propagating the attitude of EES during exo-atmospheric flight. 42 allows for a variety of spin eject mechanism scenarios to be simulated for analysis. 10 minutes prior to entry, the 42 states are handed off to the EDL sims. The prime EDL sim utilized by EES is the Program to Optimize Simulated Trajectories II (POST2), a 6-DOF sim developed at Langley Research Center, and the independent verification and validation EDL sim utilized is DSENDS, a 6-DOF sim developed at Jet Propulsion Laboratory. Figure 2 provides a visualization of the flight mechanics simulation model flow through various points in the AEDL phase. Due to the existence of a variety of sim models, the EES flight mechanics team developed processes for data hand-off. These processes included the development of a centralized coordinate frame document, utilization of a single, centralized simulation input document for all sims to reference, and hand-off files containing both the technical data to be ingested by other flight mechanics sims as well as annotations of modeling assumptions utilized to generate the data. Figure~\ref{fig:post2simarchitecture} provides an overview of the POST2 sim architecture wherein POST2 ingests numerous subsystem models and input files. The dispersed state file generated by MONTE provides the position/velocity state of the trajectory while the 42 Handoff file provides the attitude. The aerodynamics database, delivered by the EES aeroscience team, is utilized to simulate the aerodynamic forces and moments experienced during EDL. A custom atmosphere model, developed by EES atmosphere team, is utilized to simulate the anticipated atmosphere environment around the region of Earth through which the EES trajectory flys. These inputs and subsystem models can be varied depending on the AEDL flight mechanics scenario being simulated. Monte Carlo simulations are utilized to generate statistical AEDL performance metrics in the form of scorecards and violin plots. Furthermore, outputs from the POST2 simulation are utilized for follow-on analyses including aerothermal and landing performance. \section{Flight Mechanics Lessons Learned} Though the EES flight mechanics team uncovered a variety of lessons learned through the analysis conducted to support CCRS through preliminary design review, this paper will highlight the most important lessons. A key AEDL performance goal is to ensure the landing footprint of EES remains on the UTTR south range. A common modeling strategy used in EDL analysis is One-Variable-At-a-Time (OVAT). OVAT analysis provides insight into the key drivers that affect AEDL performance metrics. Figure 3 shows the landing ellipses for single dispersion sources as compared to the baseline aggregate of all dispersions. The figure shows that atmosphere winds alone dominate the size of the footprint ellipse (note: EES does not use a parachute unlike previous Earth-return missions and is in wind-driven free fall for ~5min). The significance of the wind led the EES flight mechanics team to pursue the development of a Custom Atmosphere Model [4], in lieu of EarthGRAM [1], built on actual radiosonde wind measurements around the UTTR-region. This decision was driven by the realism in the generated footprint ellipses and lessons-learned from Stardust [5]. These findings will be invaluable for future Earth-return missions in providing an early understanding of the key drivers affecting footprint size and modeling considerations for which to account. Another lesson learned is tied to the AEDL performance goal of achieving passive stability throughout all regions of flight. It is well understood that blunt-body aeroshells are less stable as they transition from supersonic to subsonic. Eliminating a backshell does help improvestability; however, other phenomena such as roll-induced instability during terminal descent can still arise. The EES flight mechanics team developed stability metrics as tools to better understand the causes of and better predict the onset of dynamic instability. These tools were built upon analytical models developed by Jaffe [3] and Murphy [2]. The tools were shown to both be very accurate in correlation with actual unstable cases and useful in developing stability margin policies based on the vehicle design and simulation considerations (e.g. sphere-cone angle change, mass change, wind turbulence). These tools allowed for the current EES design to demonstrate the ability to achieve passive stability and can be an invaluable tool for consideration in the design of parachute-less Earth-return vehicles.

Rohan Deshmukh↗

Development of Prototypical District-Scale Models: Preprint

The U.S. has set the climate goal to achieve net-zero greenhouse gas emissions by 2050. District-scale solutions, which include scale-specific opportunities for energy and emissions savings, can be investigated and implemented to help accelerate decarbonization and progress toward this goal. However, there is currently a lack of district-scale models of buildings and community energy systems that can be used to evaluate potential district-scale technologies and strategies across a range of representative community types. This initial work aims to define and develop prototype district models that can be adapted to support the planning, design, and operation of buildings and energy systems in districts considering the complexity and interactions of diverse building loads, weather impacts, distributed energy resources (e.g., PV, EV, electric and thermal energy storage), electric and thermal grid systems, and pricing signals. An overall workflow for developing these prototype district models is established. Stakeholders and potential users of the prototype district models provided technical feedback. The specifications of the selected high priority districts were defined and documented in a scorecard format. An example prototype district model was implemented with the URBANoptTM platform workflows. A case study was performed to demonstrate the model application.

district↗

Stop managing people, start managing agreements - 15081

One definition of management in business and organizations is: 'the function that coordinates the efforts of people to accomplish goals and objectives using available resources efficiently and effectively'. Unfortunately, what it takes to coordinate (literally, to create order together) is beyond the scope of today's management tools. The top five management tools in the world, according to a Bain 2013 survey, are: Strategic Planning; Customer Relationship Management; Employee Engagement Surveys; Benchmarking; and Balanced Scorecard. These are useful tools in business and organizations, but do not help managers coordinate the complex performance networks of agreements with resource providers, team members, and internal and external user-customers and authorities required to accomplish group or organizational goals. How do we manage such a network? While coordination is increasingly necessary in today's world of work, it is also a much neglected area of serious study because it is, almost literally, an invisible phenomenon. We can observe people inside groups, as well as their activities and results, but coordination is a product of managing what is going on between groups, not inside them. The challenge is making that in-between visible and actionable, not just 'white space'. A solution: define a Team's performance as agreements - and deliveries on the agreements - for products, services, and communications - the things moving between a Team and its immediate circle of resource providers, customers, and authorities relevant to a goal. This approach has been shown to reduce operational costs while also increasing team members' recognition of their interdependent responsibilities. Managers and Team leaders can then turn any Team goal into an opportunity for accomplishment in three steps: 1. Define 'performance' in terms of deliverable products, services, and communications for every goal; 2. Keep performance status current and visible to all team members; and 3. Debrief and update performance status routinely. Teamwork and engagement in goal accomplishment require a focus on Sender-Receiver agreements, productive communication, and timely and accurate status-tracking and feedback. Sustaining the context for accomplishment is not about managing people - it requires supporting coordination for the network of agreements in which people operate. (authors)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Upgrade Your Work Plans for Better Performance - 16103

Most work plans involve at least two basic pieces: a list of things to do and a timeline for doing them. These 'tasks-and-times' plans can be used for managing a project, an organizational change, or the implementation of a strategic objective. But given the high rate of plan failures - often cited as ranging from 35% to over 80% - something must be missing. Three ideas for upgrading work plans have demonstrated higher success rates than the time-and-task method alone. First, maintain a 'GPS Scorecard' of the Goals, Performance metrics, and Schedules for accomplishment. Second, maintain a Performance Circle Register of all key players, and the key deliverables to and from each of them, that will ensure success. Third, implement all three parts of an accountability management system, collectively referred to as 'T3': Tracking, Team assignments, and Talk-times to update status and progress against the plan. Why bother to take the extra steps to strengthen work plans? There are three reasons: (a) Because traveling without a map is risky in times of high change in infrastructure, staffing, and technology; (b) Because 'expectations' do not guarantee delivery as reliably as well-defined agreements; and (c) Because 'accountability' is a management practice, not a personality trait. Together, implementing these three ideas can provide for clarity of purpose, guidance in establishing the productive relationships necessary for success, and a system of supporting accountability for all participants, both on the team and with others inside and outside of the organization. (authors)

99 GENERAL AND MISCELLANEOUS↗

Strategic Planning as a Competitive Advantage by Using the BSC as a Management Tool: a Case Study in Application of Radioisotope Technology at IPEN - 16400

Strategic planning is one of the most important management tools for organizational decision making. The nuclear area represents a segment of energy production used by many countries in America, Europe and Asia. It is known that in the future nuclear energy can be a major exit to the global energy crisis. The aim of this research was to use the Balanced Scorecard (BSC) as a strategic tool for decision making in a teaching and research institution of the nuclear area - Nuclear and Energy Research Institute (IPEN), located in the city of Sao Paulo, which belongs to the National Nuclear Energy Commission (CNEN) in Brazil. The methodology used in this academic doctoral study was a case study, which considered the period of research from December 2012 to December 2015. The main results expected from this case study are: the improvement of information flow, the view, the increased visibility of an organization providing education and especially research in relation to published works, increased interaction among IPEN and the main global research institutes and centers, increasing academic production of technical articles, indicator improvement, improving the monitoring of management actions, among others. Given the expected results one can conclude that this study will be of great value to the IPEN and also for the Brazilian energy sector, as it will allow and contribute to the dissemination and demystification of nuclear power as an energy source of mankind, its peaceful applications and for the management activity of knowledge and innovation production in the nuclear area of IPEN. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗