The Range Safety Debris Catalog Analysis in Preparation for the Pad Abort One Flight Test

The Pad Abort One flight test of the Orion Abort Flight Test Program is currently under development with the goal of demonstrating the capability of the Launch Abort System. In the event of a launch failure, this system will propel the Crew Exploration Vehicle to safety. An essential component of this flight test is range safety, which ensures the security of range assets and personnel. A debris catalog analysis was done as part of a range safety data package delivered to the White Sands Missile Range in New Mexico where the test will be conducted. The analysis discusses the consequences of an overpressurization of the Abort Motor. The resulting structural failure was assumed to create a debris field of vehicle fragments that could potentially pose a hazard to the range. A statistical model was used to assemble the debris catalog of potential propellant fragments. Then, a thermodynamic, energy balance model was applied to the system in order to determine the imparted velocity to these propellant fragments. This analysis was conducted at four points along the flight trajectory to better understand the failure consequences over the entire flight. The methods used to perform this analysis are outlined in detail and the corresponding results are presented and discussed

Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation

This paper describes an algorithm for atmospheric state estimation that is based on a coupling between inertial navigation and flush air data sensing pressure measurements. In this approach, the full navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to directly estimate atmospheric winds and density using a nonlinear weighted least-squares algorithm. The approach uses a high fidelity model of atmosphere stored in table-look-up form, along with simplified models of that are propagated along the trajectory within the algorithm to provide prior estimates and covariances to aid the air data state solution. Thus, the method is essentially a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere and winds are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the discrete-time observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content to the system. The algorithm is then applied to the design of the pressure measurement system for the Mars 2020 mission. The pressure port layout is optimized to maximize the observability of atmospheric states along the trajectory. Linear covariance analysis is performed to assess estimator performance for a given pressure measurement uncertainty. The results indicate that the new tightly-coupled estimator can produce enhanced estimates of atmospheric states when compared with existing algorithms

Mars Science Laboratory Entry, Descent, and Landing Trajectory and Atmosphere Reconstruction

On August 5th 2012, The Mars Science Laboratory entry vehicle successfully entered Mars atmosphere and landed the Curiosity rover on its surface. A Kalman filter approach has been implemented to reconstruct the entry, descent, and landing trajectory based on all available data. The data sources considered in the Kalman filtering approach include the inertial measurement unit accelerations and angular rates, the terrain descent sensor, the measured landing site, orbit determination solutions for the initial conditions, and a new set of instrumentation for planetary entry reconstruction consisting of forebody pressure sensors, known as the Mars Entry Atmospheric Data System. These pressure measurements are unique for planetary entry, descent, and landing reconstruction as they enable a reconstruction of the freestream atmospheric conditions without any prior assumptions being made on the vehicle aerodynamics. Moreover, the processing of these pressure measurements in the Kalman filter approach enables the identification of atmospheric winds, which has not been accomplished in past planetary entry reconstructions. This separation of atmosphere and aerodynamics allows for aerodynamic model reconciliation and uncertainty quantification, which directly impacts future missions. This paper describes the mathematical formulation of the Kalman filtering approach, a summary of data sources and preprocessing activities, and results of the reconstruction

Mars Entry Atmospheric Data System Trajectory Reconstruction Algorithms and Flight Results

The Mars Entry Atmospheric Data System is a part of the Mars Science Laboratory, Entry, Descent, and Landing Instrumentation project. These sensors are a system of seven pressure transducers linked to ports on the entry vehicle forebody to record the pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. Specifically, angle of attack, angle of sideslip, dynamic pressure, Mach number, and freestream atmospheric properties are reconstructed from the measured pressures. Such data allows for the aerodynamics to become decoupled from the assumed atmospheric properties, allowing for enhanced trajectory reconstruction and performance analysis as well as an aerodynamic reconstruction, which has not been possible in past Mars entry reconstructions. This paper provides details of the data processing algorithms that are utilized for this purpose. The data processing algorithms include two approaches that have commonly been utilized in past planetary entry trajectory reconstruction, and a new approach for this application that makes use of the pressure measurements. The paper describes assessments of data quality and preprocessing, and results of the flight data reduction from atmospheric entry, which occurred on August 5th, 2012

The Best Estimated Trajectory Analysis for Pad Abort One

I. Best Estimated Trajectory (BET) objective: a) Produce reconstructed trajectory of the PA-1 flight to understand vehicle dynamics and aid other post flight analyses. b) Leverage all measurement sources taken of vehicle during flight to produce the most accurate estimate of vehicle trajectory. c) Generate trajectory reconstructions of the Crew Module (CM), Launch Abort System (LAS), and Forward Bay Cover (FBC). II. BET analysis was started immediately following the PA-1 mission and was completed in September, 2010 a) Quick look version of BET released 5/25/2010: initial repackaging of SIGI data. b) Preliminary version of BET released 7/6/2010: first blended solution using available sources of external measurements. c) Final version of BET released 9/1/2010: final blended solution using all available sources of data

Assessment of the Reconstructed Aerodynamics of the Mars Science Laboratory Entry Vehicle

On August 5, 2012, the Mars Science Laboratory entry vehicle successfully entered Mars atmosphere, flying a guided entry until parachute deploy. The Curiosity rover landed safely in Gale crater upon completion of the Entry Descent and Landing sequence. This paper compares the aerodynamics of the entry capsule extracted from onboard flight data, including Inertial Measurement Unit (IMU) accelerometer and rate gyro information, and heatshield surface pressure measurements. From the onboard data, static force and moment data has been extracted. This data is compared to preflight predictions. The information collected by MSL represents the most complete set of information collected during Mars entry to date. It allows the separation of aerodynamic performance from atmospheric conditions. The comparisons show the MSL aerodynamic characteristics have been identified and resolved to an accuracy better than the aerodynamic database uncertainties used in preflight simulations. A number of small anomalies have been identified and are discussed. This data will help revise aerodynamic databases for future missions and will guide computational fluid dynamics (CFD) development to improved prediction codes

Supersonic Flight Dynamics Test: Trajectory, Atmosphere, and Aerodynamics Reconstruction

The Supersonic Flight Dynamics Test is a full-scale flight test of a Supersonic Inflatable Aerodynamic Decelerator, which is part of the Low Density Supersonic Decelerator technology development project. The purpose of the project is to develop and mature aerodynamic decelerator technologies for landing large mass payloads on the surface of Mars. The technologies include a Supersonic Inflatable Aerodynamic Decelerator and Supersonic Parachutes. The first Supersonic Flight Dynamics Test occurred on June 28th, 2014 at the Pacific Missile Range Facility. This test was used to validate the test architecture for future missions. The flight was a success and, in addition, was able to acquire data on the aerodynamic performance of the supersonic inflatable decelerator. This paper describes the instrumentation, analysis techniques, and acquired flight test data utilized to reconstruct the vehicle trajectory, atmosphere, and aerodynamics. The results of the reconstruction show significantly higher lofting of the trajectory, which can partially be explained by off-nominal booster motor performance. The reconstructed vehicle force and moment coefficients fall well within pre-flight predictions. A parameter identification analysis indicates that the vehicle displayed greater aerodynamic static stability than seen in pre-flight computational predictions and ballistic range tests

The Mars Science Laboratory (MSL) Entry, Descent And Landing Instrumentation (MEDLI): Hardware Performance and Data Reconstruction

The Mars Science Laboratory (MSL) Entry, Descent and Landing Instrumentation (MEDLI) hardware was a first-of-its-kind sensor system that gathered temperature and pressure readings on the MSL heatshield during Mars entry on August 6, 2012. MEDLI began as challenging instrumentation problem, and has been a model of collaboration across multiple NASA organizations. After the culmination of almost 6 years of effort, the sensors performed extremely well, collecting data from before atmospheric interface through parachute deploy. This paper will summarize the history of the MEDLI project and hardware development, including key lessons learned that can apply to future instrumentation efforts. MEDLI returned an unprecedented amount of high-quality engineering data from a Mars entry vehicle. We will present the performance of the 3 sensor types: pressure, temperature, and isotherm tracking, as well as the performance of the custom-built sensor support electronics. A key component throughout the MEDLI project has been the ground testing and analysis effort required to understand the returned flight data. Although data analysis is ongoing through 2013, this paper will reveal some of the early findings on the aerothermodynamic environment that MSL encountered at Mars, the response of the heatshield material to that heating environment, and the aerodynamic performance of the entry vehicle. The MEDLI data results promise to challenge our engineering assumptions and revolutionize the way we account for margins in entry vehicle design

Tocotrienols are good adjuvants for developing cancer vaccines

<p>Abstract</p> <p>Background</p> <p>Dendritic cells (DCs) have the potential for cancer immunotherapy due to their ability to process and present antigens to T-cells and also in stimulating immune responses. However, DC-based vaccines have only exhibited minimal effectiveness against established tumours in mice and humans. The use of appropriate adjuvant enhances the efficacy of DC based cancer vaccines in treating tumours.</p> <p>Methods</p> <p>In this study we have used tocotrienol-rich fraction (TRF), a non-toxic natural compound, as an adjuvant to enhance the effectiveness of DC vaccines in treating mouse mammary cancers. In the mouse model, six-week-old female BALB/c mice were injected subcutaneously with DC and supplemented with oral TRF daily (DC+TRF) and DC pulsed with tumour lysate from 4T1 cells (DC+TL). Experimental mice were also injected with DC pulsed with tumour lysate and supplemented daily with oral TRF (DC+TL+TRF) while two groups of animal which were supplemented daily with carrier oil (control) and with TRF (TRF). After three times vaccination, mice were inoculated with 4T1 cells in the mammary breast pad to induce tumour.</p> <p>Results</p> <p>Our study showed that TRF in combination with DC pulsed with tumour lysate (DC+TL+TRF) injected subcutaneously significantly inhibited the growth of 4T1 mammary tumour cells as compared to control group. Analysis of cytokines production from murine splenocytes showed significant increased productions of IFN-γ and IL-12 in experimental mice (DC+TL+TRF) compared to control, mice injected with DC without TRF, mice injected with DC pulsed with tumour lysate and mice supplemented with TRF alone. Higher numbers of cytotoxic T cells (CD8) and natural killer cells (NK) were observed in the peripheral blood of TRF adjuvanted DC pulsed tumour lysate mice.</p> <p>Conclusion</p> <p>Our study show that TRF has the potential to be an adjuvant to augment DC based immunotherapy.</p