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Missouri Agricultural Energy Saving Team-A Revolutionary Opportunity (MAESTRO)

The Missouri Agricultural Energy Saving Team-A Revolutionary Opportunity (MAESTRO) program brought together a team of representatives from government, academia, and private industry to enhance the availability of energy efficiency services for small livestock producers in the State of Missouri. The Missouri Department of Agriculture (MDA) managed the project via a subcontract with the University of Missouri (MU), College of Agriculture Food and Natural Resources, MU Extension, the MU College of Human Environmental Sciences, the MU College of Engineering, and the Missouri Agricultural and Small Business Development Authority (MASBDA). MU teamed with EnSave, Inc, a nationally-recognized expert in agricultural energy efficiency to assist with marketing, outreach, provision of farm energy audits and customer service. MU also teamed with independent home contractors to facilitate energy audits of the farm buildings and homes of these livestock producers. The goals of the project were to: (1) improve the environment by reducing fossil fuel emissions and reducing the total energy used on small animal farms; (2) stimulate the economy of local and regional communities by creating or retaining jobs; and (3) improve the profitability of Missouri livestock producers by reducing their energy expenditures. Historically, Missouri scientists/engineers conducted programs on energy use in agriculture, such as in equipment, grain handling and tillage practices. The MAESTRO program was the first to focus strictly on energy efficiency associated with livestock production systems in Missouri and to investigate the applicability and potential of addressing energy efficiency in animal production from a building efficiency perspective. A. Project Objectives The goal of the MAESTRO program was to strengthen the financial viability and environmental soundness of Missouri's small animal farms by helping them implement energy efficient technologies for the production facility, farm buildings, and the homes on these farms. The expected measurable outcomes of the project were to improve the environment and stimulate the economy by: • Reducing annual fossil fuel emissions by 1,942 metric tons of carbon dioxide equivalent, reducing the total annual energy use on at least 323 small animal farms and 100 farm homes by at least 8,000 kWh and 2,343 therms per farm. • Stimulating the economy by creating or retaining at least 69 jobs, and saving small animal farmers an average of $2,071 per farm in annual energy expenditures. B. Project Scope The MAESTRO team chose the target population of small farms because while all agriculture is traditionally underserved in energy efficiency programs, small farms were particularly underserved because they lack the financial resources and access to energy efficiency technologies that larger farms deploy. The MAESTRO team reasoned that energy conservation, financial and educational programs developed while serving the agricultural community could serve as a national model for other states and their agricultural sectors. The target population was approximately 2,365 small animal farm operations in Missouri, specifically those farms that were not by definition a confined animal feeding operation (CAFO). The program was designed to create jobs by training Missouri contractors and Missouri University Extension staff how to conduct farm audits. The local economy would be stimulated by an increase in construction activity and an increasing demand for energy efficient farm equipment. Additionally, the energy savings were deemed critical in keeping Missouri farms in business. This project leveraged funds using a combination of funds from the Missouri Department of Natural Resources’ Missouri Energy Center and its Soil and Water Conservation Program, from the state's Linked Deposits, MASBDA's agricultural loan guarantee programs, and through the in-kind contribution of faculty and staff time to the project from these agencies and MU. Several hundred Missouri livestock producers were contacted during the MAESTRO project. Of the livestock producers, 254 invited the team to conduct a farm energy assessment which complied with ASABE 612. A total of 147 livestock farm upgrades were implemented, representing 57.5 percent of the farms for which a farm energy assessment was completed. This represented a statewide average annual savings of 1,088,324 kWh and 75,516 therms. The team also reviewed the condition of the livestock producer’s home(s). A total of 106 home energy assessments were completed and 48 individual homes implemented their recommended upgrades, representing 45 percent of the farm homes for which an energy assessment was completed. This represented a statewide average annual savings of 323,029 kWh, and 769.4 therms. More of these farmers likely would have updated their homes but the funding to incentivize them fell short. In spite of the shortfall in incentive funds, some farmers still updated their homes as they saw the value in making these changes to their home.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Extreme Programming: Maestro Style

"Extreme Programming: Maestro Style" is the name of a computer programming methodology that has evolved as a custom version of a methodology, called extreme programming that has been practiced in the software industry since the late 1990s. The name of this version reflects its origin in the work of the Maestro team at NASA's Jet Propulsion Laboratory that develops software for Mars exploration missions. Extreme programming is oriented toward agile development of software resting on values of simplicity, communication, testing, and aggressiveness. Extreme programming involves use of methods of rapidly building and disseminating institutional knowledge among members of a computer-programming team to give all the members a shared view that matches the view of the customers for whom the software system is to be developed. Extreme programming includes frequent planning by programmers in collaboration with customers, continually examining and rewriting code in striving for the simplest workable software designs, a system metaphor (basically, an abstraction of the system that provides easy-to-remember software-naming conventions and insight into the architecture of the system), programmers working in pairs, adherence to a set of coding standards, collaboration of customers and programmers, frequent verbal communication, frequent releases of software in small increments of development, repeated testing of the developmental software by both programmers and customers, and continuous interaction between the team and the customers. The environment in which the Maestro team works requires the team to quickly adapt to changing needs of its customers. In addition, the team cannot afford to accept unnecessary development risk. Extreme programming enables the Maestro team to remain agile and provide high-quality software and service to its customers. However, several factors in the Maestro environment have made it necessary to modify some of the conventional extreme-programming practices. The single most influential of these factors is that continuous interaction between customers and programmers is not feasible.

Norris, Jeffrey↗

Programmer's manual for the Mission Analysis Evaluation and Space Trajectory Operations program (MAESTRO)

The Mission Analysis Evaluation and Space Trajectory Operations program known as MAESTRO is described. MAESTRO is an all FORTRAN, block style, computer program designed to perform various mission control tasks. This manual is a guide to MAESTRO, providing individuals the capability of modifying the program to suit their needs. Descriptions are presented of each of the subroutines descriptions consist of input/output description, theory, subroutine description, and a flow chart where applicable. The programmer's manual also contains a detailed description of the common blocks, a subroutine cross reference map, and a general description of the program structure.

Lutzky, D.↗

Parameter estimation supplement to the Mission Analysis Evaluation and Space Trajectory Operations program (MAESTRO)

This Parameter Estimation Supplement describes the PEST computer program and gives instructions for its use in determination of lunar gravitation field coefficients. PEST was developed for use in the RAE-B lunar orbiting mission as a means of lunar field recovery. The observations processed by PEST are short-arc osculating orbital elements. These observations are the end product of an orbit determination process obtained with another program. PEST's end product it a set of harmonic coefficients to be used in long-term prediction of the lunar orbit. PEST employs some novel techniques in its estimation process, notably a square batch estimator and linear variational equations in the orbital elements (both osculating and mean) for measurement sensitivities. The program's capabilities are described, and operating instructions and input/output examples are given. PEST utilizes MAESTRO routines for its trajectory propagation. PEST's program structure and subroutines which are not common to MAESTRO are described. Some of the theoretical background information for the estimation process, and a derivation of linear variational equations for the Method 7 elements are included.

Bjorkman, W. S.↗

Sharing intelligence: Decision-making interactions between users and software in MAESTRO

By combining the best of automated and human decision-making in scheduling many advantages can accrue. The joint performance of the user and system is potentially much better than either alone. Features of the MAESTRO scheduling system serve to illustrate concepts of user/software cooperation. MAESTRO may be operated at a user-determinable and dynamic level of autonomy. Because the system allows so much flexibility in the allocation of decision-making responsibilities, and provides users with a wealth of information and other support for their own decision-making, better overall schedules may result.

Geoffroy, Amy L.↗

Preliminary results from the MAESTRO 1 Campaign over the Black Forest

The Joint Research Center (JRC) Ispra and the European Space Agency (ESA) have co-sponsored the deployment of the National Aeronautics and Space Agency (NASA) and Jet Propulsion Laboratory (JPL), C-, L-, and P-band polarimetric synthetic aperture radar (SAR) in Europe in mid-August 1989. This deployment represents the first opportunity for European agencies and institutes to evaluate the current state of the art of multifrequency polarimetric imaging technology over European Test Sites. Of particular interest to the Joint Research Center (JRC) Ispra is the Black Forest Test Site at Freiburg in the Federal Republic of Germany. This Test Site incorporates the Villingen region of the Black Forest to the south-west of Germany. This paper reports upon the activities undertaken in preparation for the MAESTRO 1 Campaign in the Black Forest Test Site. In particular this paper reports upon the ground data collection campaign for the Freiburg Test Site where extensive and intensive ground data measurements were undertaken. These measurements were based upon standard ground data collection protocols developed for forestry by the JRC and utilized throughout Europe for the MAESTRO 1 Campaign. The paper then goes on to present preliminary results derived from the SAR data using the JRC-developed software for polarimetric data interpretation, POLTOOL.

Churchill, P. N.↗

Initial SEE Testing of Maestro

We have reported on initial SEE sensitivity of the full 49-core Maestro device. Supporting the low-level structures and qualitative system observation goals of phase 1 of testing. Observed sensitivities found to be consistent with Boeing predictions. Highlighted by the L1 data cache sensitivity which drives the rates on the current Maestro device. Presented details to the hardware and software setups that show where the limitations - highlighting future work. Key future work includes testing with memory and IO ports.

cache sensitivity↗

Meeting the Challenges of Modeling Astrophysical Thermonuclear Explosions: Castro, Maestro, and the AMReX Astrophysics Suite

We describe the AMReX suite of astrophysics codes and their application to modeling problems in stellar astrophysics. Maestro is tuned to efficiently model subsonic convective flows while Castro models the highly compressible flows associated with stellar explosions. Both are built on the block-structured adaptive mesh refinement library AMReX. Together, these codes enable a thorough investigation of stellar phenomena, including Type Ia supernovae and X-ray bursts. We describe these science applications and the approach we are taking to make these codes performant on current and future many-core and GPU-based architectures.

79 ASTRONOMY AND ASTROPHYSICS↗

User's guide to the Mission Analysis Evaluation and Space Trajectory Operations program (MAESTRO)

The MAESTRO system is a mission analysis tool designed to present to the user information necessary to make the various decisions required in the design and execution of a spaceflight mission. The system was designed so that it can be used in both the pre-launch mission planning phase of a mission and during the flight as an in-flight decision making tool. A description of each of the following modes is presented: (1) trajectory propagation mode; (2) retro-fire determination mode; (3) midcourse analysis determination mode; (4) Monte Carlo mode; (5) verification mode; (6) orbit stability mode; and (7) post injection trim mode. A description of the inputs necessary to run the program mode is given along with a sample case.

Lutzky, D.↗

Managing temporal relations in the MAESTRO scheduling system

A set of viewgraphs on managing temporal relations in the MAESTRO scheduling system are given. The viewgraphs present information on such topics as why scheduling is hard, managing temporal relations, constraints on the placement of a single activity, constraints between activities, soft constraints (such as preferences), and contingency handling.

Britt, Daniel L.↗

Real-time contingency handling in MAESTRO

A scheduling and resource management system named MAESTRO was interfaced with a Space Station Module Power Management and Distribution (SSM/PMAD) breadboard at MSFC. The combined system serves to illustrate the integration of planning, scheduling, and control in a realistic, complex domain. This paper briefly describes the functional elements of the combined system, including normal and contingency operational scenarios, then focusses on the method used by the scheduler to handle real-time contingencies.

Britt, Daniel L.↗

Cliffbot Maestro

Cliffbot Maestro permits teleoperation of remote rovers for field testing in extreme environments. The application user interface provides two sets of tools for operations: stereo image browsing and command generation.

Norris, Jeffrey S.↗

Leveraging Cloud Computing to Improve Storage Durability, Availability, and Cost for MER Maestro

The Maestro for MER (Mars Exploration Rover) software is the premiere operation and activity planning software for the Mars rovers, and it is required to deliver all of the processed image products to scientists on demand. These data span multiple storage arrays sized at 2 TB, and a backup scheme ensures data is not lost. In a catastrophe, these data would currently recover at 20 GB/hour, taking several days for a restoration. A seamless solution provides access to highly durable, highly available, scalable, and cost-effective storage capabilities. This approach also employs a novel technique that enables storage of the majority of data on the cloud and some data locally. This feature is used to store the most recent data locally in order to guarantee utmost reliability in case of an outage or disconnect from the Internet. This also obviates any changes to the software that generates the most recent data set as it still has the same interface to the file system as it did before updates

Chang, George W.↗

TU-PIS-Exhibit Hall-2: Deformable Image Registration, Contour Propagation, and Dose Mapping inMIM Maestro - MIM Software

Brachytherapy devices and software are designed to last for a certain period of time. Due to a number of considerations, such as material factors, wear-and-tear, backwards compatibility, and others, they all reach a date when they are no longer supported by the manufacturer. Most of these products have a limited duration for their use, and the information is provided to the user at time of purchase. Because of issues or concerns determined by the manufacturer, certain products are retired sooner than the anticipated date, and the user is immediately notified. In these situations, the institution is facing some difficult choices: remove these products from the clinic or perform tests and continue their usage. Both of these choices come with a financial burden: replacing the product or assuming a potential medicolegal liability. This session will provide attendees with the knowledge and tools to make better decisions when facing these issues. Learning Objectives: Understand the meaning of “end-of-life or “life expectancy” for brachytherapy devices and software Review items (devices and software) affected by “end-of-life” restrictions Learn how to effectively formulate “end-of-life” policies at your institution Learn about possible implications of “end-of-life” policy Review other possible approaches to “end-of-life” issue.

60 APPLIED LIFE SCIENCES↗

maestro

MÆSTRO stands for Multi-fidelity Adaptive Ensemble Stochastic Trust Region Optimization and it is a plug n play derivate fee stochastic optimization solver. The problem being considered in MÆSTRO involves fitting Monte Carlo simulations that describe complex phenomena to experiments. This is done by finding parameters of the resource intensive and noisy simulation that yield the least squares objective function value to the noisy experimental data. This problem is solved using a stochastic trust-region optimization algorithm where in each iteration, a local approximation of the simulation signal and of the simulation noise is constructed over data, which is obtained by running the simulation at strategically placed design points within the trust-region around the current iterate. Then the simulation components of the objective are replaced by their approximations and this analytical and closed-form optimization problem is solved to find the next iterate within the trust-region. Then the trust region is moved and the iterations continue until a satisfactory convergence criteria is met.

KRISHNAMOORTHY, MOHAN↗

Comparison of edges detected at different polarisations in MAESTRO data

Edge detection would appear to be a crucial tool for analyzing multi-polarized, multi-frequency, and multi-temporal Synthetic Aperture Radar (SAR) images. Edge structure provides a simple means for comparing different polarizations and frequencies, and for detecting changes over time. Due to the fact that edges and segments (homogeneous regions) are dual concepts, edge detection has an important role to play in identifying segments within which mean backscatter measurements for use in image classification can be made. As part of a general investigation into edge detection in SAR imagery, an initial investigation was carried out into the detectability and nature of edges in multi-polarized and multi-frequency SAR images. The contrast ratio (CR) operator was used to detect edges. This operator was previously shown to perform well at detecting edges in single-polarized and single-frequency SAR images.

Caves, Ronald G.↗

Designing and Implementing a Distributed System Architecture for the Mars Rover Mission Planning Software (Maestro)

Distributed systems allow scientists from around the world to plan missions concurrently, while being updated on the revisions of their colleagues in real time. However, permitting multiple clients to simultaneously modify a single data repository can quickly lead to data corruption or inconsistent states between users. Since our message broker, the Java Message Service, does not ensure that messages will be received in the order they were published, we must implement our own numbering scheme to guarantee that changes to mission plans are performed in the correct sequence. Furthermore, distributed architectures must ensure that as new users connect to the system, they synchronize with the database without missing any messages or falling into an inconsistent state. Robust systems must also guarantee that all clients will remain synchronized with the database even in the case of multiple client failure, which can occur at any time due to lost network connections or a user's own system instability. The final design for the distributed system behind the Mars rover mission planning software fulfills all of these requirements and upon completion will be deployed to MER at the end of 2005 as well as Phoenix (2007) and MSL (2009).

Goldgof, Gregory M.↗