Water Impact Prediction Tool for Recoverable Rockets

Reusing components from a rocket launch can be cost saving. NASA's space shuttle system has reusable components that return to the Earth and impact the ocean. A primary example is the Space Shuttle Solid Rocket Booster (SRB) that descends on parachutes to the Earth after separation and impacts the ocean. Water impact generates significant structural loads that can damage the booster, so it is important to study this event in detail in the design of the recovery system. Some recent examples of damage due to water impact include the Ares I-X First Stage deformation as seen in Figure 1 and the loss of the SpaceX Falcon 9 First Stage.To ensure that a component can be recovered or that the design of the recovery system is adequate, an adequate set of structural loads is necessary for use in failure assessments. However, this task is difficult since there are many conditions that affect how a component impacts the water and the resulting structural loading that a component sees. These conditions include the angle of impact with respect to the water, the horizontal and vertical velocities, the rotation rate, the wave height and speed, and many others. There have been attempts to simulate water impact. One approach is to analyze water impact using explicit finite element techniques such as those employed by the LS-Dyna tool [1]. Though very detailed, this approach is time consuming and would not be suitable for running Monte Carlo or optimization analyses. The purpose of this paper is to describe a multi-body simulation tool that runs quickly and that captures the environments a component might see. The simulation incorporates the air and water interaction with the component, the component dynamics (i.e. modes and mode shapes), any applicable parachutes and lines, the interaction of winds and gusts, and the wave height and speed. It is capable of quickly conducting Monte Carlo studies to better capture the environments and genetic algorithm optimizations to reproduce a flight

A new approach to solving the multimode kinetics equations

Cover reads: By Joe C. Turner [sic], Allan F. HenryAlso issued as a Ph. D. thesis in the Department of Nuclear Engineering, 1972Includes bibliographical references (leaves 95-97)AEC AT(11-1)--305

Staging Survivance: Intellectual Disability, De-institutionalization, and Decolonial Arts Education

This multimedia article comprises an illustrated conversation about the context, creation, and impact of the play Birds Make Me Think About Freedom, between non-Indigenous historian and theater artist Victoria Freeman, Indigenous actor Jamie Oshkabewisens, Indigenous artist and survivor of Rideau Regional Centre in Ontario, Joe Clayton, and non-Indigenous art education professor Richard Fletcher, originally presented at the 3rd International Conference on Disability Studies, Arts & Education. This slightly revised version of the conversation about intellectual disability, de-institutionalization, and decolonial arts education through the lens of the concept and practice of survivance is accompanied by still images from the play along with other images from the Zoom conversation and details of important artworks used in the play

Generalized Logistic Models and its orthant tail dependence

The Multivariate Extreme Value distributions have shown their usefulness in environmental studies, financial and insurance mathematics. The Logistic or Gumbel-Hougaard distribution is one of the oldest multivariate extreme value models and it has been extended to asymmetric models. In this paper we introduce generalized logistic multivariate distributions. Our tools are mixtures of copulas and stable mixing variables, extending approaches in Tawn (1990), Joe and Hu (1996) and Foug\`eres et al. (2009). The parametric family of multivariate extreme value distributions considered presents a flexible dependence structure and we compute for it the multivariate tail dependence coefficients considered in Li (2009)

Economic Impact of Beef Cattle Best Management Practices in South Texas: Stocking Strategies during Drought

In a drought situation, forage is normally reduced due to lack of adequate moisture. Moreover, the availability of hay may become limited, and hay prices often escalate. Cow-calf producers are faced with the integral decision to maintain their herds and supplemental feed or reduce the herd to minimize feeding requirements and costs. The management decision to maintain versus destock can significantly impact producer profits and financial position. This paper illustrates the financial implications of alternative management stocking strategies in a drought situation optimizing profitability of ranching operations

Variational Kinetic Clustering of Complex Networks

Efficiently identifying the most important communities and key transition nodes in weighted and unweighted networks is a prevalent problem in a wide range of disciplines. Here we focus on the optimal clustering using variational kinetic parameters, linked to Markov processes defined on the underlying networks, namely the slowest relaxation time and the Kemeny constant. We derive novel relations in terms of mean first passage times for optimizing clustering via the Kemeny constant, and show that the optimal clustering boundaries have equal round-trip times to the clusters they separate.We also propose an efficient method that first projects the network nodes onto a 1D reaction coordinate and subsequently performs a variational boundary search using a parallel tempering algorithm, where the variational kinetic parameters act as an energy function to be extremized.We find that maximization of the Kemeny constant is effective in detecting communities, while the slowest relaxation time allows for detection of transition nodes.We demonstrate the validity of our method on several test systems, including synthetic networks generated from the stochastic block model and real world networks (Santa Fe Institute collaboration network, a network of co-purchased political books, and a street network of multiple cities in Luxembourg). Our approach is compared with existing clustering algorithms based on modularity and the Robust Perron Cluster Analysis and the identified transition nodes are compared with different notions of node centrality

The Use of Official Statistics in Self-Selection Bias Modeling

Official statistics are a fundamental source of publicly available information that periodically provides a great amount of data on all major areas of citizens’ lives, such as economics, social development, education, and the environment. However, these extraordinary sources of information are often neglected, especially by business and industrial statisticians. In particular, data collected from small businesses, like small and medium-sized enterprizes (SMEs), are rarely integrated with official statistics data

Skunk River Review Fall 2005, vol 17

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