scholarly journals When Field Experiments Yield Unexpected Results: Lessons Learned from Measuring Selection in White Sands Lizards

PLoS ONE ◽  
2015 ◽  
Vol 10 (2) ◽  
pp. e0118560 ◽  
Author(s):  
Kayla M. Hardwick ◽  
Luke J. Harmon ◽  
Scott D. Hardwick ◽  
Erica Bree Rosenblum
Keyword(s):  
Field Experiments ◽  
Lessons Learned ◽  
White Sands

Communication Metrics for Human-Autonomy Teaming: Lessons Learned from us Army Gunnery Field Experiments

2021 ◽  
Vol 65 (1) ◽  
pp. 1157-1161
Author(s):  
Anthony L. Baker ◽  
Sean M. Fitzhugh ◽  
Daniel E. Forster ◽  
Kristin E. Schaefer
Keyword(s):  
Field Experiments ◽  
Autonomous Systems ◽  
Lessons Learned ◽  
Critical Window ◽  
Us Army ◽  
Communication Assessment ◽  
Human Autonomy ◽  
Communication Flow ◽  
And Performance ◽  
Carry Over

The development of more effective human-autonomy teaming (HAT) will depend on the availability of validated measures of their performance. Communication provides a critical window into a team’s interactions, states, and performance, but much remains to be learned about how to successfully carry over communication measures from the human teaming context to the HAT context. Therefore, the purpose of this paper is to discuss the implementation of three communication assessment methodologies used for two Wingman Joint Capabilities Technology Demonstration field experiments. These field experiments involved Soldiers and Marines maneuvering vehicles and engaging in live-fire target gunnery, all with the assistance of intelligent autonomous systems. Crew communication data were analyzed using aggregate communication flow, relational event models, and linguistic similarity. We discuss how the assessments were implemented, what they revealed about the teaming between humans and autonomy, and lessons learned for future implementation of communication measurement approaches in the HAT context.

scholarly journals The Use of Field Experiments to Study Mechanisms of Discrimination

2016 ◽  
Vol 38 (1) ◽  
Author(s):  
Marc Keuschnigg ◽  
Tobias Wolbring
Keyword(s):  
Observational Data ◽  
Laboratory Experiments ◽  
Field Experiments ◽  
Lessons Learned ◽  
Statistical Discrimination ◽  
Differential Treatment ◽  
Experimental Designs ◽  
Social Mechanisms ◽  
Causal Pathways ◽  
Approaches To Study

AbstractThis paper discusses social mechanisms of discrimination and reviews existing field experimental designs for their identification. We first explicate two social mechanisms proposed in the literature, animus-driven and statistical discrimination, to explain differential treatment based on ascriptive characteristics. We then present common approaches to study discrimination based on observational data and laboratory experiments, discuss their strengths and weaknesses, and elaborate why unobtrusive field experiments are a promising complement. However, apart from specific methodological challenges, well-established experimental designs fail to identify the mechanisms of discrimination. Consequently, we introduce a rapidly growing strand of research which actively intervenes in market activities varying costs and information for potential perpetrators to identify causal pathways of discrimination. We end with a summary of lessons learned and a discussion of challenges that lie ahead.

scholarly journals Drivetrains on floating offshore wind turbines: lessons learned over the last 10 years

2021 ◽  
Author(s):  
Amir R. Nejad ◽  
Jone Torsvik
Keyword(s):  
Wind Turbines ◽  
Field Experiments ◽  
Structure Design ◽  
Lessons Learned ◽  
Offshore Wind ◽  
Wind Loading ◽  
Floating Offshore Wind Turbines ◽  
Induced Motion ◽  
Research Findings ◽  
Wave Induced

AbstractThis paper presents lessons learned from own research studies and field experiments with drivetrains on floating wind turbines over the last ten years. Drivetrains on floating support structures are exposed to wave-induced motions in addition to wind loading and motions. This study investigates the drivetrain-floater interactions from two different viewpoints: how drivetrain impacts the sub-structure design; and how drivetrain responses and life are affected by the floater and support structure motion. The first one is linked to the drivetrain technology and layout, while the second question addresses the influence of the wave-induced motion. The results for both perspectives are presented and discussed. Notably, it is highlighted that the effect of wave induced motions may not be as significant as the wind loading on the drivetrain responses particularly in larger turbines. Given the limited experience with floating wind turbines, however, more research is needed. The main aim with this article is to synthesize and share own research findings on the subject in the period since 2009, the year that the first full-scale floating wind turbine, Hywind Demo, entered operation in Norway.

Advantages and challenges in using mobile apps for field experiments: A systematic review and a case study

2017 ◽  
Vol 6 (2) ◽  
pp. 179-196 ◽  
Author(s):  
Jingwen Zhang ◽  
Christopher Calabrese ◽  
Jieyu Ding ◽  
Mingxuan Liu ◽  
Biying Zhang
Keyword(s):  
Systematic Review ◽  
Field Experiments ◽  
Mobile Apps ◽  
Controlled Trial ◽  
Scale Up ◽  
Lessons Learned ◽  
Design Quality ◽  
Experiment Platform ◽  
Data Limitations

As smartphone’s computing power continues to grow and as mobile applications (apps) continue to dominate digital engagement, apps have become a new frontier for advancing field experiment methodology. Using apps may help researchers to scale up the reach, precisely control randomization and experiment materials, collect a variety of objective and self-reported data over time, and more conveniently replicate and adapt an experiment. We performed a systematic review on field experiments involving apps published between 2007 and 2017. Seven databases were scanned using a predefined search strategy. The database search retrieved 4,810 citations; 101 articles met the inclusion criteria. Our review suggests that scholars have only started to employ apps in field experiments in the last 4 years. Most studies only used apps as an experiment treatment instead of an experiment platform; therefore, researchers have yet to fully leverage the advantages. Almost all studies were from the health research domain and 77.2% used randomized controlled trial design. Only 7 studies utilized smartphone sensors for collecting data. Only one study reported cost and ethical concerns regarding using apps for the experiment. Given these findings, we reported a case study that targeted a minority racial group and leveraged the advantages of apps as an experiment platform and as a data collection tool to illustrate practical challenges and lessons learned regarding time, financial cost, and technical support. In conclusion, we suggest apps provide new ways to study causal mechanisms with experiment big data. Limitations of generalizability, retention, and design quality were discussed as well.

Incorporating field wind data into FIRETEC simulations of the International Crown Fire Modeling Experiment (ICFME): preliminary lessons learned

2012 ◽  
Vol 42 (5) ◽  
pp. 879-898 ◽  
Author(s):  
Rodman Linn ◽  
Kerry Anderson ◽  
Judith Winterkamp ◽  
Alyssa Brooks ◽  
Michael Wotton ◽  
...  
Keyword(s):  
Field Experiments ◽  
Wildland Fire ◽  
Temporal Frequency ◽  
Fire Behavior ◽  
Careful Consideration ◽  
Fire Modeling ◽  
Lessons Learned ◽  
Wind Data ◽  
Crown Fire ◽  
Modeling Experiment

Field experiments are one way to develop or validate wildland fire-behavior models. It is important to consider the implications of assumptions relating to the locality of measurements with respect to the fire, the temporal frequency of the measured data, and the changes to local winds that might be caused by the experimental configuration. Twenty FIRETEC simulations of International Crown Fire Modeling Experiment (ICFME) plot 1 and plot 6 fires were performed using horizontally homogenized fuels. These simulations enable exploration of the sensitivity of model results to specific aspects of the interpretation and use of the locally measured wind data from this experiment. By shifting ignition times with respect to dynamic measured tower wind data by up to 2 min, FIRETEC simulations are used to examine possible ramifications of treating the measured tower winds as if they were precisely the same as those present at the location of the fire, as well as possible implications of temporal averaging of winds or undersampling. Model results suggest that careful consideration should be paid to the relative time scales of the wind fluctuations, duration of the fires, and data collection rates when using experimentally derived winds as inputs for fire models.

Camera Observation and Modelling of 4D Tracer Dispersion in the Atmosphere

2020 ◽  
Author(s):  
Kerstin Stebel ◽  
Massimo Cassiani ◽  
Hamidreza Ardeshiri ◽  
Cirilo Bernardo ◽  
Anna Solvejg Dinger ◽  
...  
Keyword(s):  
Field Experiments ◽  
Dimensional Space ◽  
Tomographic Reconstruction ◽  
Concentration Field ◽  
Lessons Learned ◽  
Relative Dispersion ◽  
Plume Dispersion ◽  
Tracer Concentration ◽  
Tracer Dispersion ◽  
Field Campaigns

<p>In the frame of the COMTESSA (Camera Observation and Modelling of 4D Tracer Dispersion in the Atmosphere) project, tracer dispersion release experiments were performed during three field campaigns in Norway in July 2017, 2018, and 2019.  The main goal of the project is to improve our understanding of turbulence and plume dispersion on local scale in the planetary boundary layer by bringing together full four-dimensional (space and time) observations of a (nearly) passive tracer (sulfur dioxide, SO<sub>2</sub>), with advanced data analysis and turbulence and dispersion modelling. By means of tomographic reconstruction of the 3D tracer concentration distribution, not only the mean but also higher moments of the probability density function of the tracer concentration field can be revealed. In 2017 first field tests were made, releasing SO<sub>2</sub> in continuous plumes and puffs from a 10 m tower, while in the following years SO<sub>2 </sub>was released from a 60 m tower, located in the centre of a fenced-in 900 m x 400 m wide flat gravel field. The masts were equipped with eddy covariance measurement systems to continuously record turbulent fluxes of heat and momentum during the field campaigns. Up to six ultraviolet (UV) and in 2019 also three infrared (IR) SO<sub>2</sub> cameras, were placed in a ring around the SO<sub>2 </sub>release tower at varying distances up to ~1.2 km to simultaneously image the movement and spread of the 2d integrated SO<sub>2</sub> tracer column densities.</p><p>Here we present an overview of the field experiments and lessons learned, with focus on results from the 2019 summer campaign. It was a challenge to find a location where hazardous gas could be released and a main obstacle for the imaging-based experiment were the unfavourable weather conditions. Despite these challenges, progress was made throughout the years. During consecutive summers the release equipment was improved and optimized and in 2019 puff releases were made by filling balloons with SO<sub>2</sub> and exploding them. The cameras were continuously developed, the setup of the cameras at the site was adjusted to allow observations for longer timescales.  During July 11-28, 2019 ~130 puffs were released from balloons holding between 250 g and 325 g SO<sub>2</sub>. Those are used to give an overview of the image/data processing and type of results that can be obtained from our observations, e.g. relative dispersion and meandering, Eulerian and Lagrangian integral time scales and their relation, tomographic reconstruction. The focus lies on the plume spread, i.e. relative dispersion processes we recorded under different stability conditions in July 2019.</p>

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