Zachary del Rosario
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View article: DECISIONS, VARIATION, AND VISUALIZATION: A NOVEL INSTRUMENT FOR DECISION MAKING UNDER VARIABILITY
DECISIONS, VARIATION, AND VISUALIZATION: A NOVEL INSTRUMENT FOR DECISION MAKING UNDER VARIABILITY Open
To make statistically sound choices, decision makers must respond to the consequences of variability—to target variability. Previous work has shown that targeting is beneficial, but there are questions about its prevalence and contributing…
View article: Board 190: A Mixed-Methods Study of Statistical Thinking in Engineering Practice
Board 190: A Mixed-Methods Study of Statistical Thinking in Engineering Practice Open
Variability is ubiquitous, but often ignored in engineering. Loading conditions, material properties, and human behavior all exhibit variability, but are often treated with fixed constants in engineering analysis. A first step towards impr…
View article: A Qualitative Study of Engineers’ Perception of Variability as 'Error'
A Qualitative Study of Engineers’ Perception of Variability as 'Error' Open
Variability is an unavoidable reality: People have different heights, built parts have different dimensions, and manufactured components have different material properties. It is common in statistics to refer to certain variations as "erro…
View article: A Qualitative Study of Engineering Students' Reasoning About Statistical Variability
A Qualitative Study of Engineering Students' Reasoning About Statistical Variability Open
Every aircraft you have ever flown on has been designed using probabilistically-flawed, potentially dangerous criteria (del Rosario et al. 2021, AIAA-J). That these criteria have been in use for over a half-century---but were only recently…
View article: A Scoping Review of Engineering Textbooks to Quantify the Teaching of Uncertainty
A Scoping Review of Engineering Textbooks to Quantify the Teaching of Uncertainty Open
Safe design requires that engineers consider sources of uncertainty. For instance, variability in loading conditions and material properties create a risk of structural failure. However, previous research suggests that engineers, and peopl…
View article: Board 198: A Mixed-Methods Investigation of Engineers Targeting the Consequences of Variability
Board 198: A Mixed-Methods Investigation of Engineers Targeting the Consequences of Variability Open
Variability is an unavoidable reality. Physical phenomena such as loading conditions, material properties, and human behavior all exhibit variability. Engineers must deal with this variability when designing solutions. Unfortunately, an ex…
View article: Neglected, Acknowledged, or Targeted: A Conceptual Framing of Variability, Data Analysis, and Domain Consequences
Neglected, Acknowledged, or Targeted: A Conceptual Framing of Variability, Data Analysis, and Domain Consequences Open
Variability is underemphasized in domains such as engineering. Statistics and data science education research offers a variety of frameworks for understanding variability, but new frameworks for domain applications are necessary. This stud…
View article: Quantifying uncertainty in high-throughput density functional theory: A comparison of AFLOW, Materials Project, and OQMD
Quantifying uncertainty in high-throughput density functional theory: A comparison of AFLOW, Materials Project, and OQMD Open
A central challenge in high-throughput density functional theory (HT-DFT) calculations is selecting a combination of input parameters and postprocessing techniques that can be used across all materials classes, while also managing accuracy…
View article: EVC 2022 closed codes
EVC 2022 closed codes Open
Closed codes applying the Neglected, Acknowledged, Targeted (NAT) taxonomy to the interviews described in:https://figshare.com/articles/online_resource/EVC_Interview_Guide/23552844https://figshare.com/articles/presentation/EVC_Interview_Sl…
View article: Context-Engaged Engineering Data Analysis: A Grounded Theory of Engineers Targeting the Consequences of Variability
Context-Engaged Engineering Data Analysis: A Grounded Theory of Engineers Targeting the Consequences of Variability Open
Background Variability is unavoidable in engineered systems. However, past industry failures and current practices suggest that the importance of variability is not widely understood. While prior research on variability uses a lens of stat…
View article: An Open-Source Active Learning Curriculum for Data Science in Engineering
An Open-Source Active Learning Curriculum for Data Science in Engineering Open
This work provides open-source content for an active learning curriculum in data science.The scope of the content is sufficient for a full-semester introduction to scientifically reproducible statistical computation, data wrangling, visual…
View article: Enabling Active Learning Pedagogy and Insight Mining with a Grammar of Model Analysis
Enabling Active Learning Pedagogy and Insight Mining with a Grammar of Model Analysis Open
Modern engineering models are complex, with dozens of inputs, uncertainties arising from simplifying assumptions, and dense output data. While major strides have been made in the computational scalability of complex models, relatively less…
View article: Grama: A Grammar of Model Analysis
Grama: A Grammar of Model Analysis Open
Grama is a Python package implementing a functional grammar of model analysis emphasizing the quantification of uncertainties.In Grama a model contains both a function mapping inputs to outputs as well as a distribution characterizing unce…
View article: Assessing the frontier: Active learning, model accuracy, and multi-objective candidate discovery and optimization
Assessing the frontier: Active learning, model accuracy, and multi-objective candidate discovery and optimization Open
Discovering novel chemicals and materials can be greatly accelerated by iterative machine learning-informed proposal of candidates—active learning. However, standard global error metrics for model quality are not predictive of discovery pe…
View article: Reproducibility in high-throughput density functional theory: a comparison of AFLOW, Materials Project, and OQMD
Reproducibility in high-throughput density functional theory: a comparison of AFLOW, Materials Project, and OQMD Open
A central challenge in high throughput density functional theory (HT-DFT) calculations is selecting a combination of input parameters and post-processing techniques that can be used across all materials classes, while also managing accurac…
View article: Quantifying uncertainty in high-throughput density functional theory: a comparison of AFLOW, Materials Project, and OQMD
Quantifying uncertainty in high-throughput density functional theory: a comparison of AFLOW, Materials Project, and OQMD Open
A central challenge in high throughput density functional theory (HT-DFT) calculations is selecting a combination of input parameters and post-processing techniques that can be used across all materials classes, while also managing accurac…
View article: Assessing the Frontier: Active Learning, Model Accuracy, and Multi-objective Materials Discovery and Optimization
Assessing the Frontier: Active Learning, Model Accuracy, and Multi-objective Materials Discovery and Optimization Open
Discovering novel materials can be greatly accelerated by iterative machine learning-informed proposal of candidates---active learning. However, standard \emph{global-scope error} metrics for model quality are not predictive of discovery p…
View article: Lurking Variable Detection via Dimensional Analysis
Lurking Variable Detection via Dimensional Analysis Open
Lurking variables represent hidden information, and preclude a full understanding of phenomena of interest. Detection is usually based on serendipity -- visual detection of unexplained, systematic variation. However, these approaches are d…
View article: Cutting the Double Loop: Theory and Algorithms for Reliability-Based Design Optimization with Statistical Uncertainty
Cutting the Double Loop: Theory and Algorithms for Reliability-Based Design Optimization with Statistical Uncertainty Open
Statistical uncertainties complicate engineering design -- confounding regulated design approaches, and degrading the performance of reliability efforts. The simplest means to tackle this uncertainty is double loop simulation; a nested Mon…
View article: Basis Values Have Questionable Value
Basis Values Have Questionable Value Open
Controlling the chance of failure is the aim of design for reliability. Among a host of uncertainties, material properties constitute one key input to designing safe structures. However, legally required approaches to characterizing materi…
View article: Data-driven dimensional analysis: algorithms for unique and relevant dimensionless groups
Data-driven dimensional analysis: algorithms for unique and relevant dimensionless groups Open
Classical dimensional analysis has two limitations: (i) the computed dimensionless groups are not unique, and (ii) the analysis does not measure relative importance of the dimensionless groups. We propose two algorithms for estimating uniq…
View article: Data-driven dimensional analysis: algorithms for unique and relevant\n dimensionless groups
Data-driven dimensional analysis: algorithms for unique and relevant\n dimensionless groups Open
Classical dimensional analysis has two limitations: (i) the computed\ndimensionless groups are not unique, and (ii) the analysis does not measure\nrelative importance of the dimensionless groups. We propose two algorithms for\nestimating u…
View article: Many physical laws are ridge functions
Many physical laws are ridge functions Open
A ridge function is a function of several variables that is constant along certain directions in its domain. Using classical dimensional analysis, we show that many physical laws are ridge functions; this fact yields insight into the struc…