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As the piston pin works under significant mechanical load, it is susceptible to wear, seizure, and structural failure, especially in heavy duty internal combustion engines. It has been found that the friction loss associated with the pin is comparable to that of the piston, and can be reduced when the interface geometry is properly modified. However, the mechanism that leads to such friction reduction, as well as the approaches towards further improvement, remain unknown. This work develops a piston pin lubrication model capable of simulating the interaction between the pin, the piston, and the connecting rod. The model integrates dynamics, solid contact, oil transport, and lubrication theory, and applies an efficient numerical scheme with second order accuracy to solve the highly stiff equations. As a first approach, the current model assumes every component to be rigid.

We consider the heat transfer characteristics of an ideal concentric disk used in the Wiped-Film Rotating-Disk (WFRD) evaporator for the Vapor Phase Catalytic Ammonia Removal (VPCAR) water recovery system. A mathematical model is derived to predict the radial temperature distribution and its average over the surface of the disk as a function of system parameters. The model shows self-similarity of the temperature distribution and the existence of a dimensionless parameter S (ratio of heat flux to convection) that can be used as a criterion to optimize the thermal characteristics of the disk in order to approach uniform surface temperature. Comparison of the model to experimental data using global (infrared imager) and local (resistive temperature devices) measurements shows that agreement with the model depends on the ambient condition denoted by the local heat transfer coefficient.

An extravehicular activity (EVA) path-planning and navigation tool, called the Mission Planner, has been developed to assist with pre-mission planning, scenario simulation, real-time navigation, and contingency replanning during astronaut EVAs, The Mission Planner calculates the most efficient path between user-specified waypoints. Efficiency is based on an exploration cost algorithm, which is a function of the estimated astronaut metabolic rate. Selection of waypoints and visualization of the generated path are realized within a 3D mapping interface through terrain elevation models. The Mission Planner is also capable of computing the most efficient path back home from any point along the path.

This paper describes the DC bus regulation control algorithm for the NASA flywheel energy storage system during charge, charge reduction and discharge modes of operation. The algorithm was experimentally verified in [1] and this paper presents the necessary models for simulation. Detailed block diagrams of the controller algorithm are given. It is shown that the flywheel system and the controller can be modeled in three levels of detail depending on the type of analysis required. The three models are explained and then compared using simulation results.

From November 2010 until May of 2011, NASA's Icing Remote Sensing System was positioned at Platteville, Colorado between the National Science Foundation's S-Pol radar and Colorado State University's CHILL radar (collectively known as FRONT, or ‘Front Range Observational Network Testbed’). This location was also underneath the flight-path of aircraft arriving and departing from Denver's International Airport, which allowed for comparison to pilot reports of in-flight icing. This work outlines how the NASA Icing Remote Sensing System's derived liquid water content and in-flight icing hazard profiles can be used to provide in-flight icing verification and validation during icing and non-icing scenarios with the purpose of comparing these times to profiles of polarized moment data from the two nearby research radars.

A Multi-Objective Optimization (MOO) problem concerning the thermal control problem of Multifunctional Structures (MFSs) is here addressed. In particular the use of Multi-Objective algorithms from an optimization tool and Self-Organizing Maps (SOM) is proposed for the identification of the optimal topological distribution of the heating components for a multifunctional test panel, the Advanced Bread Board (ABB). MFSs are components that conduct many functions within a single piece of hardware, shading the clearly defined boundaries that identify traditional subsystems. Generally speaking, MFSs have already proved to be a disrupting technology, especially in aeronautics and space application fields. The case study exploited in this paper refers to a demonstrator breadboard called ABB. ABB belongs to a particular subset of an extensive family of MFS, that is, of thermo-structural panels with distributed electronics and a health monitoring network.

Human explorers of planetary surfaces would benefit greatly from a spacesuit design that facilitates locomotion. To aid in the development of such an extravehicular activity suit, a design effort incorporating the concept of mechanical counter pressure (MCP) was undertaken. Three-dimensional laser scanning of the human body was used to identify the main effects of knee flexion angle on the size and shape of the leg. This laser scanning quantified the changes in shape that must be supported by an MCP garment and the tension that must be developed to produce even MCP. Evaluation of a hybrid-MCP concept using inextensible materials demonstrated strong agreement between experimental data and a mathematical model with rigid cylinder geometry. Testing of a form-fitting garment on the right lower leg of a subject demonstrated successful pressure production. Further research is required to evaluate how evenly pressure can be distributed using the hybrid-MCP concept.

Two high voltage, Series Connected Boost Regulators (SCBR) were developed to demonstrate the benefits of the SCBR topology for low Earth orbit communication satellites. The resulting breadboards had a power density of 1,200 W/kg and a measured efficiency of 95-99%. Several peak power tracking methods and algorithms were implemented to demonstrate the ability of the SCBR to peak power track a solar array. The peak power tracker derived maximum power at all times and reduced the number of sunlight battery discharges necessary. The breadboards also demonstrated several modularity techniques, which will allow a common SCBR module to be used in several applications. The breadboards were tested in an end-to-end high voltage test facility using high fidelity solar array simulators, an actual NiH2 battery, and simulated constant power loads. Design details and test results are presented.

Topology of liner finish is critical to the performance of internal combustion engines. Proper liner finish simulation processes lead to efficient engine design and research. Fourier methods have been well studied to numerically generate liner topology. However, three major issues wait to be addressed to make the generation processes feasible and reliable. First, in order to simulate real plateau honed liners, approaches should be developed to calculate accurate liner geometric parameters. These parameters are served as the input of the generation algorithm. Material ratio curve, the common geometry calculation method, should be modified so that accurate root mean square of plateau height distribution could be obtained. Second, the set of geometric parameters used in generating liner finish (ISO 13565-2) is different from the set of parameters used in manufacturing industry (ISO 13565-3). Quantitative relations between these two sets should be studied.

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding of high ice water content (HIWC) and develop onboard weather radar processing techniques to detect regions of HIWC ahead of an aircraft to enable tactical avoidance of the potentially hazardous conditions. Both HIWC RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory equipped with a Honeywell RDR-4000 weather radar and in-situ microphysical instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results. The first campaign was conducted in August 2015 with a base of operations in Ft. Lauderdale, Florida.

Three-piece oil control rings (TPOCR) are widely used in the majority of modern gasoline engines and they are critical for lubricant regulation and friction reduction. Despite their omnipresence, the TPOCRs’ motion and sealing mechanisms are not well studied. With stricter emission standards, gasoline engines are required to maintain lower oil consumption limits, since particulate emissions are strongly correlated with lubricant oil emissions. This piqued our interest in building a numerical model coupling TPOCR dynamics and oil transport to explain the physical mechanisms. In this work, a 2D dynamics model of all three pieces of the ring is built as the main frame. Oil transport in different zones are coupled into the dynamics model. Specifically, two mass-conserved fluid sub-models predict the oil movement between rail liner interface and rail groove clearance to capture the potential oil leakage through TPOCR. The model is applied on a 2D laser induced fluorescence (2D-LIF) engine.

An adaptive air/fuel ratio controller for SI engine throttle transient was developed. The scheme is based on an event- based, single- parameter fuel dynamics model. A least- square- error algorithm with an active forgetting factor was used for parameter identifications. A one- step- look- ahead controller was designed to maintain the desired air/fuel ratio by canceling the fuel dynamics with the controller setting updated adaptively according to the identified parameters. When implemented on a Ford Ztech engine and tested under a set of throttle- transient operations, the adaptive controller learned quickly and performed well.

In an engine system, the piston pin is subjected to high loading and severe lubrication conditions, and pin seizures still occur during new engine development. A better understanding of the lubricating oil behavior and the dynamics of the piston pin could lead to cost- effective solutions to mitigate these problems. However, research in this area is still limited due to the complexity of the lubrication and the pin dynamics. In this work, a numerical model that considers structure deformation and oil cavitation was developed to investigate the lubrication and dynamics of the piston pin. The model combines multi-body dynamics and elasto-hydrodynamic lubrication. A routine was established for generating and processing compliance matrices and further optimized to reduce computation time and improve the convergence of the equations. A simple built-in wear model was used to modify the pin bore and small end profiles based on the asperity contact pressures.