An official website of the United States government
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
Comparative Analysis of Pathways to Changeability
Through an examination of three cases of change in the U-2 platform, this paper compares three pathways to changeability: form changes, operational changes, and cyber changes. Each pathway can lead to change in similar properties of a system but have varying levels of performance and time to implement. For each pathway, we describe the design mechanisms necessary to implement change in that pathway. We analyze the trade-off between performance or extent of change and agility or speed of change and find that form changes offer the highest degree of changeability but take the longest time to implement. Operational changes offer the least degree of changeability but are far quicker to implement. Cyber changes lie in between these two pathways. Understanding the design choices needed and the underlying trade-off of each pathway can enable decision-makers to better select a pathway to change when the need arises. This comparative analysis is especially useful since literature has thus far examined each of these pathways in isolation, not as different paths to the same goal.
more »
« less
- Award ID(s):
- 2125677
- PAR ID:
- 10448604
- Date Published:
- Journal Name:
- Excerpt from the Proceedings of the Twentieth Annual Acquisition Research Symposium
- Page Range / eLocation ID:
- 148-159
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Anomaly-based attack detection methods depend on some form of machine learning to detect data falsification attacks in smart living cyber–physical systems. However, there is a lack of studies that consider the presence of attacks during the training phase and their effect on detection and false alarm performance. To improve the robustness of time series learning for anomaly detection, we propose a framework by modifying design choices such as regression error type and loss function type while learning the thresholds for an anomaly detection framework during the training phase. Specifically, we offer theoretical proofs on the relationship between poisoning attack strengths and how that informs the choice of loss functions used to learn the detection thresholds. This, in turn, leads to explainability of why and when our framework mitigates data poisoning and the trade-offs associated with such design changes. The theoretical results are backed by experimental results that prove attack mitigation performance with NIST-specified metrics for CPS, using real data collected from a smart metering infrastructure as a proof of concept. Thus, the contribution is a framework that guarantees security of ML and ML for security simultaneously.more » « less
-
Geographic variation in growth and reproduction trade‐offs: Implications for future tree performanceAbstract Forests play a crucial role providing ecosystem services to humans, yet many aspects of forest dynamics remain unknown. One key area is how climate change might impact reproduction of tree species. While most studies have focused on predicting tree growth, understanding how reproduction may change will be vital to forecasting future forest communities. Of particular interest is the relationship between annual growth and reproductive output, which has often been hypothesized as a trade‐off between allocating resources to growth or to reproduction. Two proposed pathways of this trade‐off, resource accumulation, that is, storage of resources over time, and resource allocation, that is, same year allocation of resources to reproduction, have been widely explored in relation to masting events. It has also been proposed that there is no internal trade‐off between the two functions, but rather there exists one or more climate variables that are intrinsically linked to both, that is, the weather hypothesis. In this study, we use 15 years of dendrochronological data and seed rain collections from forest stands at two latitudes to determine whether one or more of these strategies are taking place in two commonly occurring tree species: red maple,Acer rubrum; and sugar maple,Acer saccharum. We found evidence of a trade‐off in both species. We also found a combination of strategies was the norm, and there appeared to be evidence to also support the weather hypothesis. However, in both species, the strategy which dictated the trade‐off switched between the northern and southern regions, indicating a degree of plasticity that could be beneficial under changing environmental conditions. By identifying the ways in which growth and reproduction are connected and how these connections vary between different populations, we can gain insights into how trees allocate resources in response to changing conditions.more » « less
-
Models of well-mixed chemical reaction networks (CRNs) have provided a solid foundation for the study of programmable molecular systems, but the importance of spatial organization in such systems has increasingly been recognized. In this paper, we explore an alternative chemical computing model introduced by Qian & Winfree in 2014, the surface CRN, which uses molecules attached to a surface such that each molecule only interacts with its immediate neighbours. Expanding on the constructions in that work, we first demonstrate that surface CRNs can emulate asynchronous and synchronous deterministic cellular automata and implement continuously active Boolean logic circuits. We introduce three new techniques for enforcing synchronization within local regions, each with a different trade-off in spatial and chemical complexity. We also demonstrate that surface CRNs can manufacture complex spatial patterns from simple initial conditions and implement interesting swarm robotic behaviours using simple local rules. Throughout all example constructions of surface CRNs, we highlight the trade-off between the ability to precisely place molecules and the ability to precisely control molecular interactions. Finally, we provide a Python simulator for surface CRNs with an easy-to-use web interface, so that readers may follow along with our examples or create their own surface CRN designs.more » « less
-
Buildings consume nearly 40% of global energy and produce similar emissions. Whiletechnological advances address efficiency, occupant behavior causes energy use variations up to 300% between identical buildings. This gap between predicted and actual building performance impacts building design, operations, and grid demand management programs. Through analyses of smart thermostat data from 1,400 single-occupant homes, the researchdemonstrates that occupants respond to 8°F thermostat setpoint changes within a median of 15 minutes, while 2°F changes trigger responses within a median of 30 minutes. This highlights an understudied temporal relationship between thermostat setbacks and response time of occupant behaviors. Models of such behavior dynamics are required to incorporate occupant impacts into building performance simulation. A key contribution of this dissertation is the Thermal Frustration Theory (TFT), which positsthat thermal discomfort driven behaviors are caused by the time-accumulation of discomfort, not simply a temperature deviation threshold or a delay from an initiating event. Using a dataset of 634 thermostats, each with 25+ manual setpoint changes, a comparative analysis of TFT and comfort zone and a delayed response theories demonstrated that personalized TFT models better predict when manual setpoint change occur. This was measured by the area under the curve statistical measure (AUC); all three models perform similarly by a Matthews Correlation Coefficient measure. Higher AUC performance is especially important for modeling occupant behavior in demand response programs where false negatives of rare occupant interactions could adversely affect grid stability. EnergyPlus based simulations were conducted with TFT-derived occupant models, demonstrating the ability to identify parameters of known TFT models from only data observable with smart thermostats, even under the presence of noise from routine overrides. Overall, the dissertation highlights that thermostat interactions are neither static,instantaneous, nor driven solely by the environment. Instead, temporal accumulation of discomfort and routine-based behavior play important roles. The methodology and results offer a pathway towards more accurate modeling of human-building interactions for policy assessment, building design, and demand response programs.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
