Power consumption is a growing concern in the design of computing platforms, particularly large-scale, HPC systems or computing platforms that assist battlefield operations. Accordingly, Intel® recently introduced a new development platform, Software Development Platform S2R2 Family with Intel® Node Manager technology, that is capable of real-time dynamic power monitoring and capping. Although targeted at data centers, such a tool can be applied to one compute node. This development opens up new possibilities for managing payloads in fielded computing platforms, which typically have limited power budgets. Towards this end, this paper presents a preliminary study of the effect of node power capping on the execution time of two applications of interest to the U.S. Army. We executed the applications under a range of power caps and employed performance counters and a program that strides through memory invoking different levels of the hierarchy to capture execution time as well as other performance metrics that help explain the increase in execution times with heightened restrictions on power consumption. Confirming results of earlier work, we show that, in general, time-to-solution and energy consumption increase as the power cap decreases. In addition, our data indicates that: (1) for fielded systems there is a range of power caps that may result in acceptable increases in execution time and (2) although power capping is achieved mainly by dynamic voltage and frequency scaling (DVFS), when executing at lower power caps other techniques are being employed to reduce power consumption.