Study of Uncertainties of Predicting Space Shuttle Thermal Environment

Quantitative estimates of the uncertainty in predicting aerodynamic heating rates for a fully reusable space shuttle system are developed and the impact of these uncertainties on Thermal Protection System (TPS) weight are discussed. The study approach consisted of statistical evaluations of the scatter of heating data on shuttle configurations about state-of-the-art heating prediction methods to define the uncertainty in these heating predictions. The uncertainties were then applied as heating rate increments to the nominal predicted heating rate to define the uncertainty in TPS weight. Separate evaluations were made for the booster and orbiter, for trajectories which included boost through reentry and touchdown. For purposes of analysis, the vehicle configuration is divided into areas in which a given prediction method is expected to apply, and separate uncertainty factors and corresponding uncertainty in TPS weight derived for each area

Aerothermodynamic Assessment of Corrugated Panel Thermal Protection Systems

The feasibility of using corrugated panels as a thermal protection system for an advanced space transportation vehicle was investigated. The study consisted of two major tasks: development of improved correlations for wind tunnel heat transfer and pressure data to yield design techniques, and application of the design techniques to determine if corrugated panels have application future aerospace vehicles. A single-stage-to-orbit vehicle was used to assess advantages and aerothermodynamic penalties associated with use of such panels. In the correlation task, experimental turbulent heat transfer and pressure data obtained on corrugation roughened surfaces during wind tunnel testing were analyzed and compared with flat plate data. The correlations and data comparisons included the effects of a large range of geometric, inviscid flow, internal boundary layer, and bulk boundary layer parameters in supersonic and hypersonic flow

Association of interest, attitude and learning habit in mathematics learning towards enhancing students’ achievement

Mathematics is fundamentally important for Science and Technology, as well as in engineering. Mathematics is compulsory for students since all engineering subjects were Mathematically oriented. However, the preliminary study found that students’ achievement in Mathematics courses have been associated with three main factors, namely interest, attitude and learning habit, as in the KASH Model (Knowledge, Attitude, Skills and Habits). This Model stipulated that poor performance is not just lacking in knowledge and skills but also including poor attitude and habits. Therefore, this study aims to investigate the students’ level and relationship between interest, attitude and learning habit based on KASH Model. A total of 58 students were selected as a sample of the study, who enrolled in the Thermodynamics, Fluid Mechanics and Solid Mechanics subjects. A set of questionnaires with 21 items was used to collect data; a descriptively analysis was used to find the mean and percentage, as well as correlation index using Pearson. The results; high level of factor of interest, attitude and learning habit, and high correlation between interest, attitude and habit. The implication is that teaching and learning process must equally fostering all these variables to achieve a high level of students’ achievement, especially in Mathematics subjects

Implementation of Simulation Software on Vocational High School Students in Programming and Arduino Microcontroller Subject

The purpose of this study is to determine students’ learning performance who underwent simulation software class on the Programming and Arduino Microcontroller Subject. A quasi-experimental study, with pretest and posttest design was implemented. The subject involved 74 vocational high school students (37 in the control group and 37 in the experimental group) have undergone eight weeks of treatment, using conventional and Proteus simulation software. Students’ performance was measured using achievement test; involved cognitive, psychomotor, and affective aspect, which was based on the Bloom’s Taxonomy. The result indicated that students in the experimental group have outperformed their counterpart in the control group in cognitive aspect (81.4 vs 76.24), affective aspect (81.83 vs 76.34) and psychomotor aspect (79.04 vs 70.37). Further analysis using independent t-test, result indicated that the experimental group’s performance has significantly difference from the control group’s performance at all aspects [t(72) = 3.068, p = .004]. In conclusion, simulation software using Proteus has a significant contribution to increase students’ performance in learning. The implication is that, teaching difficult subject involves programming of microcontroller should use simulation software, so that students become more enthusiast, have many choices in experimenting and capable of nurturing creativity. Future study suggested to focus on the effect of simulation software on nurturing specific creativity skills

Carbon Consequences of Forest Disturbance and Recovery Across the Conterminous United States

Forests of North America are thought to constitute a significant long term sink for atmospheric carbon. The United States Forest Service Forest Inventory and Analysis (FIA) program has developed a large data base of stock changes derived from consecutive estimates of growing stock volume in the US. These data reveal a large and relatively stable increase in forest carbon stocks over the last two decades or more. The mechanisms underlying this national increase in forest stocks may include recovery of forests from past disturbances, net increases in forest area, and growth enhancement driven by climate or fertilization by CO2 and Nitrogen. Here we estimate the forest recovery component of the observed stock changes using FIA data on the age structure of US forests and carbon stocks as a function of age. The latter are used to parameterize forest disturbance and recovery processes in a carbon cycle model. We then apply resulting disturbance/recovery dynamics to landscapes and regions based on the forest age distributions. The analysis centers on 28 representative climate settings spread about forested regions of the conterminous US. We estimate carbon fluxes for each region and propagate uncertainties in calibration data through to the predicted fluxes. The largest recovery-driven carbon sinks are found in the South central, Pacific Northwest, and Pacific Southwest regions, with spatially averaged net ecosystem productivity (NEP) of about 100 g C / square m / a driven by forest age structure. Carbon sinks from recovery in the Northeast and Northern Lake States remain moderate to large owing to the legacy of historical clearing and relatively low modern disturbance rates from harvest and fire. At the continental scale, we find a conterminous U.S. forest NEP of only 0.16 Pg C/a from age structure in 2005, or only 0.047 Pg C/a of forest stock change after accounting for fire emissions and harvest transfers. Recent estimates of NEP derived from inventory stock change, harvest, and fire data show twice the NEP sink we derive from forest age distributions. We discuss possible reasons for the discrepancies including modeling errors and the possibility of climate and/or fertilization (CO2 or N) growth enhancements

Faster subsequence recognition in compressed strings

Computation on compressed strings is one of the key approaches to processing massive data sets. We consider local subsequence recognition problems on strings compressed by straight-line programs (SLP), which is closely related to Lempel--Ziv compression. For an SLP-compressed text of length $\bar m$, and an uncompressed pattern of length $n$, C{\'e}gielski et al. gave an algorithm for local subsequence recognition running in time $O(\bar mn^2 \log n)$. We improve the running time to $O(\bar mn^{1.5})$. Our algorithm can also be used to compute the longest common subsequence between a compressed text and an uncompressed pattern in time $O(\bar mn^{1.5})$; the same problem with a compressed pattern is known to be NP-hard

Dynamic Set Intersection

Consider the problem of maintaining a family $F$ of dynamic sets subject to insertions, deletions, and set-intersection reporting queries: given $S,S'\in F$, report every member of $S\cap S'$ in any order. We show that in the word RAM model, where $w$ is the word size, given a cap $d$ on the maximum size of any set, we can support set intersection queries in $O(\frac{d}{w/\log^2 w})$ expected time, and updates in $O(\log w)$ expected time. Using this algorithm we can list all $t$ triangles of a graph $G=(V,E)$ in $O(m+\frac{m\alpha}{w/\log^2 w} +t)$ expected time, where $m=|E|$ and $\alpha$ is the arboricity of $G$. This improves a 30-year old triangle enumeration algorithm of Chiba and Nishizeki running in $O(m \alpha)$ time. We provide an incremental data structure on $F$ that supports intersection {\em witness} queries, where we only need to find {\em one} $e\in S\cap S'$. Both queries and insertions take O\paren{\sqrt \frac{N}{w/\log^2 w}} expected time, where $N=\sum_{S\in F} |S|$. Finally, we provide time/space tradeoffs for the fully dynamic set intersection reporting problem. Using $M$ words of space, each update costs $O(\sqrt {M \log N})$ expected time, each reporting query costs $O(\frac{N\sqrt{\log N}}{\sqrt M}\sqrt{op+1})$ expected time where $op$ is the size of the output, and each witness query costs $O(\frac{N\sqrt{\log N}}{\sqrt M} + \log N)$ expected time.Comment: Accepted to WADS 201

Estimating the value of watershed services following forest restoration

Declining forest health, climate change, and development threaten the sustainability of water supplies in the western United States. While forest restoration may buffer threats to watershed services, funding shortfalls for landscape-scale restoration efforts limit management action. The hydrologic response and reduction in risk to watersheds following forest restoration treatments could create significant nonmarket benefits for downstream water users. Historic experimental watershed studies indicate a significant and positive response from forest thinning by a reallocation of water from evapotranspiration to surface-water yield. In this study, we estimate the willingness to pay (WTP) for improved watershed services for one group of downstream users, irrigators, following forest restoration activities. We find a positive and statistically significant WTP within our sample of $183.50 per household, at an aggregated benefit of more than$400,000 annually for 2181 irrigators. Our benefit estimate provides evidence that downstream irrigators may be willing to invest in landscape-scale forest restoration to maintain watershed services