The authors present a Full Paper in the Research-To-Practice category. Educational institutions are increasingly looking toward diversity, equity, and inclusion initiatives as a means of addressing inequities with regards to student representation rates and outcomes. We recognize that the field of engineering was historically designed and continues to operate for the benefit of straight, cis, white, affluent men. Often, institutions offer supplemental programming to students who do not embody this set of identities as a means of support, seeking to more effectively integrate them into fundamentally inequitable structures. Typically, due to the top-down nature of this supplemental programming, it presents additional barriers to challenging the existence of these structures or empowering students to enact equity-centered change. Alternatively, we sought to design a program for marginalized engineering students that reduced barriers to the expression of their whole selves, including the value of their identities within the engineering educational space. Applying critical and liberative theoretical frameworks, we invited marginalized students to organize within themselves to enact changes to even the most fundamental aspects of the existing educational structure. This program, the Undergraduate Engineering Collaborative Growth Series, was implemented at a large, prestigious research university in the United States and monetarily paid students for the labor associated with their participation. It consisted of a series of workshops that aimed to support the development of a community that recognized commonalities across experiences and organized to meet their collective needs. This paper discusses the methods used to recruit and select participants for the series as well as outlines facilitation and data collection methods. The collected data forms the basis for ongoing research. In the future, we hope to expand the program to reach more students in more programs at more institutions. In doing so, the intention is to support the empowerment of marginalized students, the best experts in their own experiences, to connect forms of power to action that disrupts the barriers currently preventing them from expressing their whole, authentic selves within engineering academia.

The authors present a Research Full Paper on the application of critical and liberative theories in understanding the disproportionately low student outcomes of marginalized undergraduate students studying engineering at a large, highly selective public university in the United States. In addition to looking at women students and students of color, we also examine the effects of social class on educational opportunity and performance, hypothesizing that access to financial capital is correlated to student success. In recognition of class-related structural oppression, this study introduces the framework of Freirean critical theory and other anti-oppressive frameworks as lenses through which we observe and analyze student experiences and outcomes.We pursue a quantitative study in which we investigate engineering student outcomes based on reported gender, ethnicity, and household income level. Dependent variables include degree completion rates, time to graduation, and grade point average after the first four semesters of study. We find that students of color and working class students experience lower rates of graduation, prolonged time to degree, and lower grade point averages than students who do not fall into either of these categories. These results are heavily influenced by the intersectionality of students of color and working class students, as the two groups largely overlap both in the United States population and in the engineering student body at this institution.The results support liberative theoretical claims that societal structures, such as patriarchalism, racism, and capitalism, have filtering effects that impact the opportunities available to individuals with marginalized identities throughout their lives. As incremental interventions fail to address the roots of these problems, they cannot entirely remove the debilitating obstacles facing students from marginalized identity groups; the only true solution lies in liberation from oppressive social structures. In accordance with critical and liberative theories, engineering educators can and should contribute to liberative efforts by employing pedagogical methods that challenge structural oppression.

One of the ways that the Sun interacts with the Earth is through the solar wind, which is an ionized multi-component fluid that emanates from the Sun and travels radially outward at hundreds of kilometers per second. Solar-wind transients, such as Coronal Mass Ejections (CME's), can be particularly important. In rare cases, CME's have affected the lower atmosphere of the Earth, causing regional power-grid failures. More regularly, CME's pose threats to satellites and spacecraft. Due to the extreme range of temporal and spatial scales involved in solar-wind phenomena, it had previously been impossible to predict CME propagation to Earth with faster-than-real-time, well-resolved calculations. Our team has now developed a highly scalable solution-adaptive scheme for predicting CME propagation. The solution-adaptive technique is an adaptive mesh refinement (AMR) scheme for magneto- hydrodynamic (MHD) calculations. The physical domain is decomposed into three- dimensional blocks, where each block forms a regular grid. In regions of relatively high gradients, blocks are successively refined. Blocks are distributed to processors, with communication between neighboring blocks is handled by asynchronous message passing. The benchmark calculation achieved 212 Gflops on a 1024-processor Cray T3E-1200, with the grid adapting over the course of the calculation from 2048 blocks to 11,729 blocks, where each block was composed of 10x10x10 cells. On a 512-processor Cray T3E-600, our benchmark simulations were performed 16 times faster than real time.

We examine a data structure which uses flexible "adaptivity" to obtain high performance for both serial and parallel computers. The data structure is an adaptive grid which partitions a given region into regular cells. Its closest relatives are cell-based tree decompositions, but there are several important differences which lead to significant performance advantages. Using this block data structure to support adaptive mesh refinement (AMR), we were able to sustain 17 GFLOPS in ideal magnetohydrodynamic (MHD) simulations of the solar wind emanating from the base of the solar corona, using a 512 processor Cray T3D at NASA Goddard.