Daniel Selva

Texas A&M University | TAMU · Department of Aerospace Engineering

Heuristics and meta-heuristics are often used to solve complex real-world problems such as the non-linear, non-convex, and multi-objective combinatorial optimization problems that regularly appear in system design and architecture. Unfortunately, the performance of a specific heuristic is largely dependent on the specific problem at hand. Moreover,...

Architecting large complex systems is a challenging task due to the presence of uncertainty, ambiguity, and subjectivity as well as the extremely large space of candidate architectures. While the traditional approach to system architecting is a 100% human process, there has been a relatively recent trend to incorporate computational tools to differ...

A key step of the mission development process is the selection of a system architecture, i.e., the layout of the major high-level system design decisions. This step typically involves the identification of a set of candidate architectures and a cost-benefit analysis to compare them. Computational tools have been used in the past to bring rigor and...

In less than a decade, Cubesats have evolved from purely educational tools to a standard platform for technology demonstration and scientific instrumentation. The use of COTS (Commercial-Off-The-Shelf) components and the ongoing miniaturization of several technologies have already led to scattered instances of missions with promising scientific val...

Design Space Exploration (DSE) is a knowledge acquisition technique used from early-stage to detailed engineering design. During DSE, designers systematically generate a range of design alternatives and compare them by their design criteria. DSE allows designers to learn about the design problem, e.g., about design decisions or features that are mo...

Design space exploration is a method for gaining insights into a space of design alternatives to make important design decisions. Current research in design space exploration is studying the use of Artificial Intelligence (AI) agents (called cognitive assistants) to provide cognitive support to human designers and help them obtain insights from lar...

Design heuristics are traditionally used as qualitative principles to guide the design process, but they have also been used to improve the efficiency of design optimization. Using design heuristics as soft constraints or search operators has been shown for some problems to reduce the number of function evaluations needed to achieve a certain level...

In early satellite mission design, requirements are not yet fixed, cost is sometimes negotiable, and designs are relatively unconstrained. During this period of design freedom, multi-objective optimization can provide a useful lens into the design space by showing theoretical performance limits and illuminating design tradeoffs. This work optimizes...

Deep generative models have shown significant promise in improving performance in design space exploration. But there is limited understanding of their interpretability, a necessity when model explanations are desired and problems are ill-defined. Interpretability involves learning design features behind design performance, called designer learning...

Deep generative models have shown significant promise to improve performance in design space exploration (DSE), but they lack interpretability. A component of interpretability in DSE is helping designers learn how input design decisions influence multi-objective performance. This experimental study explores how human-machine collaboration influence...

This work presents a patent mining methodology to qualitatively examine functional evolution of engineered products. Using a topic modeling method called Nonnegative Matrix Factorization, topics of nutcracker- and drone-related patents of different time frames are automatically generated to understand how the two products have functionally evolved...

Design space exploration is a design method by which the designer tries to learn important information about a design problem (e.g., main design trade-offs, sensitivities, common features among good designs) to help them make better design decisions. This paper presents preliminary results of a study characterizing the effects on a designer’s learn...

Artificial Intelligence (AI) agents have the potential to play a critical role in human spaceflight by being the first point of contact for astronauts during emergencies in a long duration spaceflight mission, when communication delays with the Mission Control Crew (MCC) become longer and more frequent. Sharing some of tasks done by the MCC with an on-...

With the recent advances in satellite miniaturization, communication and information technologies, and the advent of affordable small satellite launch services, there has been a paradigm shift in space exploration missions involving the transition from monolithic architectures formed by a large satellite to the concept of Distributed Spacecraft Mis...

Designing planetary entry, descent, and landing (EDL) systems requires analyzing large datasets containing tens of thousands of parameters. These datasets are generally manually analyzed by subject-matter experts trying to find interesting correlations and couplings between parameters that explain the behaviors observed. A popular approach to autom...

Lattice-based mechanical metamaterials can be tailored for a wide variety of applications by modifying the underlying mesostructure. However, most existing lattice patterns take symmetry as a starting point. We show that asymmetric lattice patterns can be more likely to have certain mechanical properties than symmetric lattice patterns. To directly...

The success of future lunar missions depends on quality positioning, navigation, and timing (PNT) information. Earthbound GNSS signals can be received at lunar distances but suffer from poor geometric dilution of precision (GDOP) and provide no coverage of the lunar far side. This article explores the design space of a dedicated GNSS system in luna...

This paper studies the effects on learning and performance for a human using a virtual assistant to perform a design space exploration task—design a satellite constellation for Earth Observation. We conducted a study at Texas A&M University with N = 18 STEM students, who were asked to use two versions of an assistant to perform the task. One versio...

View Video Presentation: https://doi.org/10.2514/6.2022-1182.vid Representing end-to-end science traceability from high-level scientific goals or questions all the way to instrument and platform requirements is of key importance, especially in the early phases of mission development. In the context of program formulation and mission portfolio selec...

View Video Presentation: https://doi.org/10.2514/6.2022-0925.vid In recent years, decision trees have been an uncommon approach to design space exploration, and meta-heuristics and machine learning have been the primary approach. Although these approaches have proven effective, decision trees have the unique property that allows us to explicitly tr...

Artificial Intelligence (AI) has had a strong presence in engineering design for decades, and while theory, methods, and tools for engineering design have advanced significantly during this time, many grand challenges remain. Modern advancements in AI, including new strategies for capturing, storing, and analyzing data, have the potential to revolu...

Lattice-based mechanical metamaterials can be tailored for a wide variety of applications by modifying the underlying mesostructure. However, most existing lattice patterns take symmetry as a starting point. We show that asymmetric lattice patterns can be more likely to have certain mechanical properties than symmetric lattice patterns. To directly...

Design space exploration (DSE) is an important knowledge discovery process in the early design phase of complex systems. The outcomes of this process generally include the performance of the designs generated and designer learning. The latter broadly refers to the designer's knowledge of the mapping between the design space and the objective space....

Design optimization of metamaterials and other complex systems often relies on the use of computationally expensive models. This makes it challenging to use global multi-objective optimization approaches that require many function evaluations. Engineers often have heuristics or rules of thumb with potential to drastically reduce the number of funct...

The purpose of this paper is to propose a new method for the automatic composition of both encoding schemes and search operators for system architecture optimization. The method leverages prior work that identified a set of six patterns that appear often in system architecture decision problems (down-selecting, combining, assigning, partitioning, p...

This paper presents a framework to describe and explain human-machine collaborative design focusing on Design Space Exploration (DSE), which is a popular method used in the early design of complex systems with roots in the well-known design as exploration paradigm. The human designer and a cognitive design assistant are both modeled as intelligent...

Delay tolerant networks (DTNs) offer a set of standardized protocols to enable Internet-like connectivity across the solar system. Unlike other protocols such as the Transmission Control Protocol (TCP) and the Internet Protocol (IP), DTN protocols are robust to end-to-end connection disruptions and long delays. Although the behavior of DTN core pro...

Currently, the observation plans for most Earth observation satellites are static and periodic, and centrally uploaded from ground control. When there is an event of interest that requires changing the plan, new plans are manually patched and uploaded to the spacecraft. This approach is limited in that: 1) it may lead to missing short-lived phenome...

Clouds are an obstacle for many remote sensing applications. Earth observation satellites may have repeat cycles that allow for study of temporal variations, but for certain types of instruments, high cloud fractions can make the time gap between high quality observations unacceptably long. On-board image processing has recently been implemented on...

Delay Tolerant Networking (DTN) offers a set of standardized protocols to enable Internet-like connectivity across the Solar System. Unlike other networking protocols such as TCP and IP, which assume continuous connection between source and destination, DTN protocols are robust to end-to-end connection disruptions and long delays. While the core pr...

The past decade has witnessed a growing interest in lunar exploration missions. The autonomy of lunar surface and in-orbit missions is, however, dependent on accurate and instantaneous navigation services. These services can not be provided by current Global Navigation Satellite Systems (GNSS) whose signals suffer from poor geometry and coverage in...

While there exist various knowledge discovery tools to support designers’ learning during design space exploration, there is no established definition of what is expected to be learned and how it should be measured. Measuring learning is important, as it enables assessing and comparing different knowledge discovery methods. In this paper, we review...

Global Navigation Satellite Systems (GNSS) provide ubiquitous, continuous and reliable positioning, navigation and timing information around the world. However, GNSS space segment design decisions have been based on the precursor Global Positioning System (GPS), which was designed in the 70s. This paper revisits those early design decisions in view...

D-SHIELD is a suite of scalable software tools that helps schedule payload operations of a large constellation, with multiple payloads per and across spacecraft, such that the collection of observational data and their downlink, constrained by the constellation constraints (orbital mechanics), resources (e.g., power) and subsystems (e.g., attitude...

Global Navigation Satellite Systems (GNSS) provide ubiquitous, continuous and reliable positioning, navigation and timing information around the world. However, GNSS space segment design decisions have been based on the precursor Global Positioning System (GPS), which was designed in the 70s. This paper revisits those early design decisions in view...

This article describes Daphne, a virtual assistant for designing Earth observation distributed spacecraft missions. It is, to the best of our knowledge, the first virtual assistant for such application. The article provides a thorough description of Daphne, including its question answering system and the main features we have implemented to help sy...

The early-phase design of complex systems is a challenging task, as a decision maker has to take into account the intricate relationships among different design variables. A popular way to help decision makers easily identify important design features is to use data mining. However, many of the existing algorithms output design features that are to...

This paper studies the trade-offs between two metrics that play a key role in the design of Global Navigation Satellite System (GNSS) architectures: Dilution Of Precision (DOP) and cost. DOP is a multiplicative factor that quantifies the satellite-user geometric diversity and sets the limit on the achievable User Navigation Error (UNE). We focus on...

Entry, Descent and Landing (EDL) architecture performance and uncertainty analysis relies heavily on end-to-end simulation given that EDL system verification and validation is limited in Earth environments. Overall system assessment and success criteria evaluation are performed by employing Monte Carlo dispersion analysis. These simulations produce...

The orbit and constellation design process for Earth observation missions is complex and it involves trades between mission lifetime, instrument performance, coverage, cost, and robustness among others. This paper describes an orbit and constellation design study conducted during Pre-Phase A and Phase A for the NASA-funded Time-Resolved Observation...

Cognitive differences between how people perceive and process information have been broadly studied in the fields of education and psychology. Previous findings show that comprehension is optimized when information presentation aligns with the cognitive abilities and preferences of an individual. On the other hand, the possession of field knowledge...

In this paper, we introduce the concept of exploring the feature space to aid learning in the context of design space exploration. The feature space is defined as a possible set of features mapped in a 2D plane with each axis representing different interestingness measures, such as precision or recall. Similar to how a designer explores the design...

We present a digital–physical system to support human–computer collaborative design. The system consists of a sensor-instrumented “sand table” functioning as a tangible space for exploring early-stage design decisions.

We present a digital-physical system to support side-by-side collabora-tive human-computer design exploration. The system consists of a sensor-instrumented "sand table" functioning as a digital-tangible space for exploring early-stage design decisions. Using our system, the human designer generates phyiscal representations of design solutions, whil...

Cognitive differences between how people perceive and process information have been broadly studied in the fields of education and psychology. Previous findings show that comprehension is optimized when information presentation aligns with the cognitive abilities and preferences of an individual. On the other hand, the possession of field knowledge...

Graph theory is used across systems science and engineering to obtain insights about the structure of complex systems. For example, in Stakeholder Value Networks (SVN), graphs are used to model stakeholders and their value exchanges. Centrality measures can thus be used to help the systems engineer prioritize among stakeholder needs. SVN have docum...

As distributed satellite systems gain interest, there is a growing need for design tools that can identify system architectures with good trades in multiple metrics. Evolutionary algorithms have shown promise as effective design-support tools but are computationally inefficient because they require evaluating many architectures before identifying o...

In this era of the “big data revolution,” the desired capabilities of Earth Observing Systems are growing fast: we need ever more frequent data sets, covering a larger part of the frequency spectrum, with lower latency, and higher spatial resolution. To better address these needs, the space systems community has been exploring the value of shifting...

Despite their limited lifespan and reduced cost, nanosatellite missions have proved to be suitable platforms for Earth observation, scientific experiments, and technology demonstration. During the last years, the number of nanosatellite missions has noticeably increased, posing the need to improve several system characteristics to ultimately endors...

Knowledge-intensive evolutionary algorithms (EA) and knowledge-driven optimization algorithms that leverage problem- or domain-specific knowledge have been shown to discover high-quality solutions with fewer function evaluations than knowledge-independent EAs. Knowledge-intensive EAs apply the available knowledge through 1) knowledge-dependent oper...

Adaptive operator selection (AOS) is a high-level controller for an optimization algorithm that monitors the performance of a set of operators with a credit assignment strategy and adaptively applies the high performing operators with an operator selection strategy. AOS can improve the overall performance of an optimization algorithm across a wide...

Despite years of research efforts developing methods and decision support tools, architecting complex engineered systems remains a challenging task. Improvements in computational power and optimization algorithms have made it possible to explore large design spaces, but making sense of such datasets is difficult due to their scale and complexity. V...

In the design of aerospace systems, it is important to understand both the tradeoffs between desired objectives and the mapping between design decisions and objectives. In this work, we present a nonparametric analysis technique that combines clustering and matching to find " minimal change sets " which define a hierarchy of design commitment. In d...

This paper proposes a set of six canonical classes of architectural decisions derived from the tasks described in the system architecture body of knowledge and from real system architecture problems. These patterns can be useful in modeling architectural decisions in a wide range of complex engineering systems. They lead to intelligible problem for...

Evolutionary algorithms have shown much success in solving real-world design problems, but they are considered computationally inefficient because they rely on many objective-function evaluations instead of leveraging domain knowledge to guide the optimization. An evolutionary algorithm’s performance can be improved by utilizing operators called do...

One of the major challenges faced by the decision maker in the design of complex engineering systems is information overload. When the size and dimensionality of the data exceeds a certain level, a designer may become overwhelmed and no longer be able to perceive and analyze the underlying dynamics of the design problem at hand, which can result in...

In the early-phase design of complex systems, a model of design performance is coupled with visualizations of competing designs and used to aid human decision-makers in finding and understanding an optimal design. This consists of understanding the tradeoffs among multiple criteria of a "good" design and the features of good designs. Current visual...

Methods to design space communication networks at the link level are well understood and abound in the literature. Nevertheless, models that analyze the performance and cost of the entire network are scarce, and they typically rely on computationally expensive simulations that can only be applied to specific network designs. This paper presents an...