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A Proposed Process to Define and Collect Project Information for Cost Estimation of CubeSat Platforms
No full textCost estimation is a key element in the planning and execution of CubeSat mission, as it helps ensure that resources are used efficiently and that mission objectives remain aligned with technical and operational constraints. A solid technical baseline - one that clearly describes the system’s characteristics - is essential for developing reliable cost estimates and for establishing a shared understanding of the project among stakeholders. This paper presents the cost estimation process used at the ITA Space Center for CubeSat platforms. The method follows a structured, eight-step approach adapted from NASA and ESA standards. The steps begin with receiving the stakeholder\u27s request and understanding the project’s purpose. Next, a Work Breakdown Structure (WBS) is defined or obtained. In the third step, technical project information is gathered or reviewed. The fourth step involves building the cost model based on the chosen methodology. Step five focuses on collecting supporting data, which is followed by the actual cost estimation in step six. The seventh step addresses the analysis of risks and uncertainties. Finally, in the eighth step, the cost estimate is revised after design reviews to incorporate updates and changes. The paper focuses specifically on Step 3, where the technical baseline is defined. This step involves collecting and verifying project data, identifying system characteristics, and tracking technical milestones. This part of the process is particularly important for improving the accuracy and consistency of cost projections, especially for research and educational missions. To build this baseline, parameters such as satellite mass, mission type and duration, orbital profile, propulsion needs, power requirements, data rate, and attitude control specifications are collected. The parameters are selected and refined through discussions with subject-matter experts to reflect the specific needs of the CubeSats developed at ITA. An important aspect of this process is the close collaboration between the estimation team and the technical leaders. This ensures that the information used for cost modeling is up to date and reflects the actual system configuration. Additionally, the process considers the interdependencies between subsystems and external constraints, such as launcher compatibility and payload objectives, to improve overall estimate quality. The approach is illustrated through its application to SPORT; a space weather CubeSat developed at the ITA Space Center. The case study shows how Step 3 contributes to a more reliable cost estimate by grounding it in realistic and well-documented technical assumptions. This paper aims to contribute to the improvement of cost estimation practices for CubeSats and other small satellite missions, offering a process that is structured yet flexible enough to be adapted to projects with similar technical and operational characteristics
Improving Retention and Knowledge Continuity in University CubeSat Laboratories
No full textThe Laboratory for Advanced Space Systems at Illinois (LASSI) at the University of Illinois Urbana-Champaign (UIUC) trains students from diverse engineering disciplines in CubeSat design and mission development. Despite offering hands-on experience and industry-like training, LASSI previously faced challenges retaining students, particularly after the first semester. Knowledge gaps in these students and the loss of expertise in technical areas, such as software development and electrical engineering, in graduating senior members contributed to retention losses. This paper discusses strategies implemented to address these challenges, their measurable impacts, and the lessons learned during implementation. In 2019, LASSI transitioned from a student organization to a new curriculum-based model, creating a more structured learning environment to foster accountability and responsibility. Foundational CubeSat principles were introduced through lectures and coursework targeted at first-, second-, and third-year students, with students encouraged to pursue lab work independently. By 2021, LASSI split course time between classroom instruction and laboratory work, dedicating one day each week to applied learning. Students were expected to complete lab assignments outside of class hours, encouraging active engagement. Since restructuring, retention rates have increased from 11% in 2019 to 73% in 2025, and lab participation rates have improved significantly. The Protege Program was introduced in 2021 to address knowledge retention and expertise continuity. This mentorship initiative assigns students to subsystem teams (e.g., flight software, communications, structures, etc.), each led by a senior student or graduate mentor. Team leaders provide direct mentorship, ensuring expertise is passed down as senior members graduate. The program has grown from seven students in 2019 to fifteen students in 2025, with 100% of students indicating in surveys that mentorship enhanced their confidence and ability to contribute meaningfully to projects. While these efforts have produced measurable improvements, challenges remain. Balancing classroom and lab time has been difficult for students managing heavy course loads, leading to occasional drops in engagement. Additionally, team leaders reported struggles with the added responsibility of mentoring while managing their own tasks. To address these challenges, LASSI has allowed more flexibility with student\u27s schedules. Students can now meet with their separate groups outside of class time. These adjustments have contributed to sustained engagement and knowledge retention without overburdening participants. Results show that 88.9% of students feel that their work contributes meaningfully to real missions, and retention after the first semester of the Protégé Program being implemented has increased from 42.8% in 2021 to 73% in 2025. Students also report greater confidence in their technical and leadership skills, which better prepares them for aerospace careers. This paper provides a detailed overview of LASSI’s curriculum and mentorship programs, highlights implementation challenges, and demonstrates the broader impact of these strategies on university CubeSat mission success. The model serves as a blueprint for other academic programs seeking to improve retention, engagement, and knowledge continuity in aerospace education
Optical Telescope Paradigms for High-Performance Cost-Effective SmallSats
Get PDFZERODUR®’s supreme thermo-mechanical stability is enabling for high-performance telescopes, including mirror substrates and even the precision metering structure. For on-orbit high-resolution SmallSat telescopes, tight dimensional control may be passively maintained, even while experiencing continuously changing Solar and Earth thermal view factors. This stability is a vast improvement over implementation in alternate materials like aluminum. ZERODUR®’s thermal and strength characteristics are comprehensively described via ~ 100 scientific publications. Innate stability, decades of spaceborne heritage and expert machining and lightweighting from SCHOTT offers special ZERODUR® cost-effective solutions for SmallSat Telescope Design-to-Cost paradigms, even for constellation level implementation. The latest information for such designs is described, including that for designing with ZERODUR®’s thermal ultrastability, with its comprehensive strength data, with its lightweighting, and even with ultrastable, cost-effective all-ZERODUR® structures. A paradigm proven capable of reducing the time and cost in optical fabrication by up to 50% is summarized. Other key characteristics, for example demisability, radiation resilience, mounting mirrors and even EAR/ITAR supply chain management will be described
Big Data Solutions for CubeSat Mission Operations: A Case Study From the Michigan eXploration Lab
Get PDFAs space missions generate increasingly vast and complex datasets, efficient data management and processing solutions are critical. At the Michigan eXploration Lab (MXL) at the University of Michigan, where we design, build, and operate CubeSats, we have adopted big data technologies, specifically a Hadoop and Spark-based cluster, to address challenges in handling and analyzing large-scale data. These challenges include processing raw I/Q sample recordings from CubeSat satellite passes and suborbital missions, as well as mission-long spacecraft telemetry. The cluster leverages the distributed storage capabilities of the Hadoop Distributed File System (HDFS) and the in-memory data processing power of Apache Spark, supported by Apache Hive for structured data management. Additionally, we developed a custom Out-of-Tree (OOT) module for GNU Radio, enabling seamless read/write operations to and from HDFS directly within the GNU Radio environment. This module introduces two blocks: HDFS Sink and HDFS Source, which mimic the built-in File Sink and File Source blocks but interact with HDFS. Published on our lab’s GitHub as a contribution to the community, this module extends the versatility of GNU Radio in handling large-scale data workflows. This paper explores the motivation behind adopting big data tools, details the cluster’s hardware and software setup, and presents current applications, including processing radio signal data, analyzing telemetry, and supporting an on-premises machine learning platform as a data lake. These advancements demonstrate the transformative potential of scalable, data-driven engineering in space systems. The paper concludes with a discussion of the challenges encountered in implementing these technologies and an outlook on future directions for the developed cluster
Target Selection for the Pandora SmallSat: A NASA Mission to Disentangle Stellar and Exoplanet Atmosphere Signals
Get PDFThe Pandora SmallSat mission was selected for implementation in 2021 as part of NASA’s Astrophysics Pioneers Program. Pandora is designed to monitor stellar variability while studying the atmospheres of transiting exoplanets via transmission spectroscopy. The transmission spectroscopy technique is one of the best methods to identify the makeup of exoplanetary atmospheres now and in the coming decade. However, stellar variations that occur from the presence of, for example, cool star spots, have been shown to contaminate the exoplanet atmosphere spectra obtained with high-precision transmission spectroscopy measurements. This stellar contamination leads to ambiguous interpretations when attempting to distinguish features like potential water vapor absorption signatures in the exoplanet atmosphere from the presence of water vapor in the host star atmosphere. Pandora will address the problem of stellar contamination by collecting long-duration photometric observations with a visible-light channel and simultaneous spectra with a near-infrared channel. These simultaneous multiwavelength observations will constrain star spot covering fractions of exoplanet host stars, enabling star and planet signals to be disentangled in transmission spectra to then reliably determine exoplanet atmosphere compositions. The Pandora science team employs a systematic process to optimize the selection of 20 transiting exoplanet targets for Pandora to observe in its prime mission, with the exoplanet sizes ranging from Earth- to Jupiter-size and host stars spanning primarily K and M spectral types. Transiting exoplanet targets are chosen strategically in order to meet science requirements for the prime mission while also enabling synergies with science from other ground- and space-based facilities. With Pandora’s observational capabilities, auxiliary science observations of non-exoplanet targets are also feasible.
Pandora is on track for launch readiness in Fall 2025. Following launch on a SpaceX Falcon 9 rocket and a month-long commissioning period, Pandora will have a prime mission of one year
Evaluation of Diet Quality, Physical Health, And Mental Health Baseline Data From a Wellness Intervention for Individuals Living in Transitional Housing
Get PDFBackground/Objectives: The aim of this study was to evaluate baseline health measurements among transitional housing residents (n = 29) participating in an 8-week pilot wellness intervention. Methods: Researchers measured anthropometrics, body composition, muscular strength, cardiovascular indicators, physical activity, diet quality, and health-related perceptions. Researchers analyzed data using descriptive statistics and conventional content analysis. Results: Most participants were male, White, and food insecure. Mean BMI (31.8 ± 8.6 kg/m2 ), waist-to-hip ratio (1.0 ± 0.1 males, 0.9 ± 0.1 females), body fat percentage (25.8 ± 6.1% males, 40.5 ± 9.4% females), blood pressure (131.8 ± 17.9/85.2 ± 13.3 mmHg), and daily step counts exceeded recommended levels. Absolute grip strength (77.1 ± 19.4 kg males, 53.0 ± 15.7 kg females) and perceived general health were below reference standards. The Healthy Eating Index-2020 score (39.7/100) indicated low diet quality. Common barriers to healthy eating were financial constraints (29.6%) and limited cooking/storage facilities (29.6%), as well as to exercise, physical impediments (14.8%). Conclusions: Residents living in transitional housing have less favorable body composition, diet, and grip strength measures, putting them at risk for negative health outcomes. Wellness interventions aimed at promoting improved health-related outcomes while addressing common barriers to proper diet and exercise among transitional housing residents are warranted
The Socioecology of Indigenous Archaeological Maize in the Uinta Basin, Utah
Get PDFThis thesis investigates the phenotypic variability of maize (Zea mays spp.) from archaeological sites located in the Uinta Basin, Utah. Maize was first introduced to the American Southwest around 5,000 years ago following its migration via trade routes from its native region of southern Mexico (Vint 2017). The adaptation of maize to the arid and temperate conditions of the American Southwest and Mexico triggered significant phenotypic change resulting from human and environmental selection pressures. This thesis focuses on the analysis of uncharred maize cobs from seven archaeological sites in the Uinta Basin. The analysis includes 70 corn cobs—most of which are well-preserved— including 22 that have been radiocarbon dated. Additionally, this thesis examines variation in maize cob attributes over time and considers the implications of population dynamics, productivity and innovation on this variability. The results of this study indicate that there is phenotypic variability in Uinta Basin archaeological maize spanning A.D. 300 to 1100, coinciding with successive demographic transitions. This study provides a meaningful addition to limited research on maize in the region and the existing research on maize varieties south of the study area
Integrating EEG and Pupillometry to Investigate Reward Learning With Neutral Feedback
No full textWhile the brain\u27s response to positive and negative feedback is well understood, neutral feedback, where outcomes are neither positive (such as a reward) nor negative (such as a loss), remains largely unexplored. How does the brain interpret and learn from neutral outcomes? This study aimed to answer that question by combining electroencephalography (EEG), a neuroimaging technique, and pupillometry, an eye-tracking technique, to investigate the brain\u27s response to neutral feedback and how it differs from rewards and losses.
Participants completed a computer-based task called Beat the Dealer , where they selected one of two cards and received feedback on whether they beat the dealer (win), lost to the dealer (loss), or tied the dealer (neutral outcome). Unbeknownst to participants, the outcomes were pre-determined, so certain outcomes were more likely in different blocks. For example, in one block, ties were rare, while in another, they were the most common. This design allowed for measuring how the brain and pupils responded to neutral outcomes depending on their probability and context.
Results suggest that neutral feedback is not inherently categorized as good or bad, but rather, its meaning depends on context and expectation. When neutral feedback was rare, it was processed more like a loss. However, when neutral feedback was expected, it was processed as an intermediate signal rather than a negative one. This study also revealed that pupil dilation, a measure linked to norepinephrine, which is a neuromodulator involved in attention and learning, played an important role in shaping how the brain responded to feedback. Larger pupil dilations were associated with better differentiation between expected and unexpected outcomes, highlighting the role of norepinephrine when learning from feedback.
These findings challenge the traditional binary model of decision-making and suggest that neutral feedback can serve as a meaningful learning signal. Understanding how the brain processes neutral feedback could have important implications for psychology, behavioral economics, and clinical neuroscience, particularly in conditions like depression and anxiety where feedback learning is disrupted. By integrating EEG and pupillometry, this study provides new insights into how dopamine and norepinephrine interact to shape learning and decision-making
A Value Sensitive Design Approach to Reimagining Parental Control Apps
Get PDFParental control apps are often used by families to regulate children\u27s device usage and keep them safe online. However, existing tools focus on monitoring and restricting children, which can lead to tension and mistrust within families. This research takes a new approach by exploring how parental control apps can be redesigned to support positive family values, like encouraging open communication between parents and children and helping children self-regulate their behaviors. Through four in-depth studies, this dissertation looks at how these values play out in different real-life situations. It includes families with children on the autism spectrum, divorced households where parents may not always agree, developmentally age-appropriate designs, and field deployment in real-world contexts. Each study helps us better understand what families need from these apps and how we can design them to fit those needs. For example, parents of autistic children may benefit from apps that offer more structure and use simple, clear language. Divorced parents may need tools that help them coordinate rules or share responsibilities. And children of different ages need different kinds of support; what works for a 6-year-old would not work for a teenager. To sum up, this research shows that good parental control apps are not just about limiting device usage; they are about building trust, reducing conflict, and empowering both parents and children to grow together in the digital age
Cognitive Behavioral Therapy Complemented With Emotion Regulation Training for Patients With Somatic Symptom Disorder: 3-Year Follow-Up to a Randomized Controlled Trial
Get PDFThis manuscript is a 3-year follow-up analysis of a multicenter, randomized, parallel group, controlled trial (N = 254) employed with individuals struggling with somatic symptom disorder (SSD; Kleinstäuber et al., 2019) comparing the effects of cognitive behavioral therapy (CBT) alone and enriching cognitive behavioral therapy with emotion regulation training (ENCERT). Results from Kleinstäuber et al. (2019) suggested that both of these interventions were similarly efficacious for SSD for symptom severity (primary outcome), with moderate to large effects at post treatment and 6-month follow-up. Further analysis of secondary outcomes and moderation effects demonstrated results suggesting ENCERT was superior to CBT-SOMA for the emotion regulation skills of emotional understanding and emotional acceptance, as well more generally for individuals with comorbid psychological disorders (anxiety and depression).
Our 3-year follow up results continued to demonstrate both CBT and ENCERT efficacy for SSD, with positive improvements in symptom severity and nearly all secondary outcomes maintaining their impacts between post-treatment and 3-year follow- up with non-significant differences between groups. Moderator analysis at this time-point did not indicate that either intervention was more helpful than the other for individuals with comorbidity. The most novel and important finding from this follow-up analysis was how lasting treatment impacts were for both of these groups over this long period of time. Future research is needed to determine if these long-term impacts are indicated in other studies and deeper evaluations of the most germane mechanisms of change for SSD improvement are indicated as an effort to better understand differentiations between CBT and emotion regulation training