An official website of the United States government
Abstract Infrastructure systems must change to match the growing complexity of the environments they operate in. Yet the models of governance and the core technologies they rely on are structured around models of relative long-term stability that appear increasingly insufficient and even problematic. As the environments in which infrastructure function become more complex, infrastructure systems must adapt to develop a repertoire of responses sufficient to respond to the increasing variety of conditions and challenges. Whereas in the past infrastructure leadership and system design has emphasized organization strategies that primarily focus on exploitation (e.g., efficiency and production, amenable to conditions of stability), in the future they must create space for exploration, the innovation of what the organization is and does. They will need to create the abilities to maintain themselves in the face of growing complexity by creating the knowledge, processes, and technologies necessary to engage environment complexity. We refer to this capacity asinfrastructure autopoiesis. In doing so infrastructure organizations should focus on four key tenets. First, a shift to sustained adaptation—perpetual change in the face of destabilizing conditions often marked by uncertainty—and away from rigid processes and technologies is necessary. Second, infrastructure organizations should pursue restructuring their bureaucracies to distribute more resources and decisionmaking capacity horizontally, across the organization’s hierarchy. Third, they should build capacity for horizon scanning, the process of systematically searching the environment for opportunities and threats. Fourth, they should emphasize loose fit design, the flexibility of assets to pivot function as the environment changes. The inability to engage with complexity can be expected to result in a decoupling between what our infrastructure systems can do and what we need them to do, and autopoietic capabilities may help close this gap by creating the conditions for a sufficient repertoire to emerge.
more »
« less
Understanding Post-Production Change and Its Implications for System Design: A Case Study in Close Air Support During Desert Storm
Complex engineered systems with long life cycles can expect to face operational uncertainty. Two common approaches to maintain system performance in an uncertain operating environment are flexibility, where the system is designed to change easily in response to a change in the operating environment and robustness, where the system is designed to sustain performance despite change. Prior work has examined how to design systems to be either flexible or robust, but so far this work largely assumes that these strategies are implemented during the design phase and that designers know the possible changes that the system will face. However, in practice, many systems face unforeseeable needs and must be modified to sustain value post-production. Through an inductive case study, this paper examines that process: documenting how aircraft were modified post-production to gain new capabilities for close air support in Operation Desert Storm. Consistent with prior studies, it finds that new capabilities can be gained through both changes to form and changes to tactics. Extending this line of work, this study examines the conditions under which each type of change is effective. Additionally, it highlights an important interaction between form and tactical changes that has not been well defined in existing literature.
more »
« less
- Award ID(s):
- 2125677
- PAR ID:
- 10448606
- Date Published:
- Journal Name:
- Naval engineers journal
- Volume:
- 134
- Issue:
- 3
- ISSN:
- 0028-1425
- Page Range / eLocation ID:
- 87-95
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)This paper focuses on the empirical derivation of regret bounds for mobile systems that can vary their locations within a spatiotemporally varying environment in order to maximize performance. In particular, the paper focuses on an airborne wind energy system, where the replacement of towers with tethers and a lifting body allows the system to adjust its altitude continuously, with the goal of operating at the altitude that maximizes net power production. While prior publications have proposed control strategies for this problem, often with favorable results based on simulations that use real wind data, they lack any theoretical or statistical performance guarantees. In the present work, we make use of a very large synthetic data set, identified through parameters from real wind data, to derive probabilistic bounds on the difference between optimal and actual performance, termed regret. The results are presented for a variety of control strategies, including a maximum probability of improvement, upper confidence bound, greedy, and constant altitude approaches.more » « less
-
The task of automatically assessing and adjusting image quality, when capturing face images using any band-specific camera sensor, can be achieved by eliminating a variety of acquisition parameters such as illumination. One such parameter related to image quality is sharpness. If it is not accurately estimated during data collection, it may affect the quality of the overall face image dataset and thus face recognition accuracy. While manually focusing each camera on the target (human face) can result in sharp looking face images, the process can be cumbersome for the operators and the subjects and, thus, it increases data collection acquisition time. In this work, we developed an electromechanical based system that automatically assesses face image sharpness, prior to capture rather than necessitating post-processing schemes. Various blur quality factors and constraints have been empirically evaluated, before determining the algorithmic steps of our proposed system. This paper discusses the implementation of this system in a live operating system.more » « less
-
Higher education faces a number of wicked problems, including the inequitable work environment for non-tenure-track faculty (NTTF), that require innovative solutions. This study examines the potential of liberatory design thinking for creating new policies, programs, and practices in higher education, including how the professional bureaucratic environment might shape the design process. Using data from three campuses where changes related to NTTF were successfully implemented, we extend the conceptualization of design thinking toward a model that adapts existing phases of design thinking and identifies new phases where the work of design is particularly influenced by the higher education context. We identify three dimensions that particularly contribute to these differences: politics and power in professional bureaucracies, structural and cultural constraints, and centering equity. This model has practical implications for supporting equity-minded change processes in higher education and may be of particular interest to policymakers, institutional leaders, design teams, and researchers.more » « less
-
A key challenge faced by small and medium-sized business entities is securely managing software updates and changes. Specifically, with rapidly evolving cybersecurity threats, changes/updates/patches to software systems are necessary to stay ahead of emerging threats and are often mandated by regulators or statutory authorities to counter these. However, security patches/updates require stress testing before they can be released in the production system. Stress testing in production environments is risky and poses security threats. Large businesses usually have a non-production environment where such changes can be made and tested before being released into production. Smaller businesses do not have such facilities. In this work, we show how “digital twins”, especially for a mix of IT and IoT environments, can be created on the cloud. These digital twins act as a non-production environment where changes can be applied, and the system can be securely tested before patch release. Additionally, the non-production digital twin can be used to collect system data and run stress tests on the environment, both manually and automatically. In this paper, we show how using a small sample of real data/interactions, Generative Artificial Intelligence (AI) models can be used to generate testing scenarios to check for points of failure.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- The DOI is not currently available.
